| Home | << 1 2 3 4 5 6 7 8 9 10 >> [11–11] |
|
| Records | |||||
|---|---|---|---|---|---|
Author  |
Thomas Ludwig; Christian Reuter; Ralf Heukäufer; Volkmar Pipek | ||||
| Title | CoTable: Collaborative Social Media Analysis with Multi-Touch Tables | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
| Volume | Issue | Pages | |||
| Keywords | Collaboration; CSCW; multi-touch tables; social media | ||||
| Abstract | To be able to take efficient measures in crisis management, it is essential for emergency services to get as much details about an actual situation on-site as possible. Currently content from social media plays an important role since those platforms are used to spread crisis-relevant data within the population. Our contribution presents a concept which supports the situation assessment practices of emergency services by collaboratively evaluating and by analyzing citizen-generated content from social media using a multi-touch table. The concept was implemented based on a Microsoft PixelSense and evaluated with 14 participants. The results reveal the impact of subjectivity of the participants, their positioning around the table as well as the uniqueness of social media posts on the collaborative situation assessment with multi-touch tables. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1228 | |||
| Share this record to Facebook | |||||
| Author |
Thomas Papadimos; Nick Pantelidis; Stelios Andreadis; Aristeidis Bozas; Ilias Gialampoukidis; Stefanos Vrochidis; Ioannis Kompatsiaris | ||||
| Title | Real-time Alert Framework for Fire Incidents Using Multimodal Event Detection on Social Media Streams | Type | Conference Article | ||
| Year | 2022 | Publication | ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2022 |
| Volume | Issue | Pages | 623-635 | ||
| Keywords | Alert framework; social media; event detection; kernel density estimation; community detection | ||||
| Abstract | The frequency of wildfires is growing day by day due to vastly climate changes. Forest fires can have a severe impact on human lives and the environment, which can be minimised if the population has early and accurate warning mechanisms. To date, social media are able to contribute to early warning with the additional, crowd-sourced information they can provide to the emergency response workers during a crisis event. Nevertheless, the detection of real-world fire incidents using social media data, while filtering out the unavoidable noise, remains a challenging task. In this paper, we present an alert framework for the real-time detection of fire events and we propose a novel multimodal event detection model, which fuses both probabilistic and graph methodologies and is evaluated on the largest fires in Spain during 2019. | ||||
| Address | Centre for Research & Technology Hellas Information Technologies Institute Thessaloniki, Greece;Centre for Research & Technology Hellas Information Technologies Institute Thessaloniki, Greece;Centre for Research & Technology Hellas Information Technologie | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Tarbes, France | Editor | Rob Grace; Hossein Baharmand | |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-82-8427-099-9 | Medium | |
| Track | Social Media for Crisis Management | Expedition | Conference | ||
| Notes | Approved | no | |||
| Call Number | ISCRAM @ idladmin @ | Serial | 2443 | ||
| Share this record to Facebook | |||||
| Author |
Thomas Spielhofer; Anna Sophie Hahne; Christian Reuter; Marc-André Kaufhold; Stefka Schmid | ||||
| Title | Social Media Use in Emergencies of Citizens in the United Kingdom | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages | |||
| Keywords | Emergencies; social media; Twitter; Facebook; representative study | ||||
| Abstract | People use social media in various ways including looking for or sharing information during crises or emergencies (e.g. floods, storms, terrorist attacks). Few studies have focused on European citizens? perceptions, and just one has deployed a representative sample to examine this. This article presents the results of one of the first representative studies on this topic conducted in the United Kingdom. The study shows that around a third (34%) have used social media during an emergency and that such use is more widespread among younger people. In contrast, the main reasons for not using social media in an emergency include technological concerns and that the trustworthiness of social media content is doubtful. However, there is a growing trend towards increased use. The article deduces and explores implications of these findings, including problems potentially arising with more citizens sharing information on social media during emergencies and expecting a response. |
||||
| Address | Technische Universität Darmstadt, Science and Technology for Peace and Security (PEASEC), Germany;The Tavistock Institute of Human Relations (TIHR) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1849 | |||
| Share this record to Facebook | |||||
| Author |
Tiberiu Sosea; Iustin Sirbu; Cornelia Caragea; Doina Caragea; Traian Rebedea | ||||
| Title | Using the Image-Text Relationship to Improve Multimodal Disaster Tweet Classification | Type | Conference Article | ||
| Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
| Volume | Issue | Pages | 691-704 | ||
| Keywords | Multi-modal disaster tweet classification, Image-text coherence relationship prediction, ViLBERT | ||||
| Abstract | In this paper, we show that the text-image relationship of disaster tweets can be used to improve the classification of tweets from emergency situations. To this end, we introduce DisRel, a dataset which contains 4,600 multimodal tweets, collected during the disasters that hit the USA in 2017, and manually annotated with coherence image-text relationships, such as Similar and Complementary. We explore multiple models to detect these relationships and perform a comprehensive analysis into the robustness of these methods. Based on these models, we build a simple feature augmentation approach that can leverage the text-image relationship. We test our methods on 2 tasks in CrisisMMD: Humanitarian Categories and Damage Assessment, and observe an increase in the performance of the relationship-aware methods. | ||||
| Address | University of Illinois at Chicago; University Politehnica of Bucharest; University of Illinois at Chicago; Kansas State University; University Politehnica of Bucharest | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
| Track | Social Media for Disaster Response and Resilience | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
| Notes | tsosea2@uic.edu | Approved | no | ||
| Call Number | ISCRAM @ idladmin @ | Serial | 2365 | ||
| Share this record to Facebook | |||||
| Author |
Tom Duffy; Richard McMaster; Chris Baber; Robert Houghton | ||||
| Title | Towards an ontology broker to improve cross-agency sharing in emergency response | Type | Conference Article | ||
| Year | 2012 | Publication | ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2012 |
| Volume | Issue | Pages | |||
| Keywords | Disasters; Information services; Information systems; Terrorism; Communication and collaborations; Disaster response; Emergency response; Information networks; Organisational boundaries; Shared understanding; Socio-technical networks; Standard operating procedures; Emergency services | ||||
| Abstract | Major incidents and disasters tend to be highly complex, contain high levels of uncertainty and may often force official responders to set aside their standard operating procedures and work collaboratively with a range of agencies and actors on the ground. Prior work has shown that establishing clear lines of communication and maintaining a shared understanding across organisational boundaries can be challenging to achieve, particularly in stressful and unusual circumstances. In the present paper we discuss ongoing work into specifying a meta-process for facilitating communication and collaboration based on the observation that common themes that emerge in communication within and across organisational boundaries can subsequently be tracked and built into an Ontology Broker. This work draws on experimental work in our laboratory, observations made in emergency control environments and, emphasised in this paper, lessons learned in the 2005 London bombings. © 2012 ISCRAM. | ||||
| Address | University of Birmingham, United Kingdom; University of Nottingham, United Kingdom | ||||
| Corporate Author | Thesis | ||||
| Publisher | Simon Fraser University | Place of Publication | Vancouver, BC | Editor | L. Rothkrantz, J. Ristvej, Z.Franco |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9780864913326 | Medium | |
| Track | Social Media and Collaborative Systems | Expedition | Conference | 9th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 103 | |||
| Share this record to Facebook | |||||
| Author |
Tom Wilson; Stephanie A. Stanek; Emma S. Spiro; Kate Starbird | ||||
| Title | Language Limitations in Rumor Research? Comparing French and English Tweets Sent During the 2015 Paris Attacks | Type | Conference Article | ||
| Year | 2017 | Publication | Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2017 |
| Volume | Issue | Pages | 546-553 | ||
| Keywords | social media; rumoring, language; crisis informatics; information diffusion | ||||
| Abstract | The ubiquity of social media facilitates widespread participation in crises. As individuals converge online to understand a developing situation, rumors can emerge. Little is currently known about how online rumoring behavior varies by language. Exploring a rumor from the 2015 Paris Attacks, we investigate Twitter rumoring behaviors across two languages: French, the primary language of the affected population; and English, the dominant language of Internet communication. We utilize mixed methods to qualitatively code and quantitatively analyze rumoring behaviors across French and English language tweets. Most interestingly, temporal engagement in the rumor varies across languages, but proportions of tweets affirming and denying a rumor are very similar. Analyzing tweet deletions and retweet counts, we find slight (but not significant) differences between languages. This work offers insight into potential limitations of previous research of online rumoring, which often focused exclusively on English language content, and demonstrates the importance of considering language in future work. | ||||
| Address | Human Centered Design and Engineering, University of Washington ; Information School, Department of Sociology, University of Washington | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Albi, France | Editor | Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | Medium | ||
| Track | Social Media Studies | Expedition | Conference | 14th International Conference on Information Systems for Crisis Response And Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 2042 | |||
| Share this record to Facebook | |||||
| Author |
Torben Wiedenhöfer; Christian Reuter; Benedikt Ley; Volkmar Pipek | ||||
| Title | Inter-organizational crisis management infrastructures for electrical power breakdowns | Type | Conference Article | ||
| Year | 2011 | Publication | 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011 | Abbreviated Journal | ISCRAM 2011 |
| Volume | Issue | Pages | |||
| Keywords | Information systems; Risk management; Software engineering; Citizen participation; Coordination process; Crisis management; Emergency management; Inter-organizational; Inter-organizational learning; Software engineering process; User centered designs; Outages | ||||
| Abstract | Major electricity breakdowns like the Northeast Blackout (USA) in 2003 or the blackout in most parts of Western Europe in 2005, have shown the fundamental role of electricity in our everyday life. The experiences of these accidents show that power suppliers, firefighters, police, county administration and citizens face multifarious challenges in inter-organizational communication, information and coordination processes during coping and recovery work. In this work-in-progress paper we describe early research dealing with inter-organizational issues in emergency management (EM). We are mainly focusing on supporting social practices in inter-organizational EM, for example collaborative interpretation of emergency situations, ad-hoc coordination or supporting citizen communication and helping routines. Identified from our experiences from related projects, discussions and literature studies, we suggest potential questions and future topics in user-driven software engineering processes for EM and domain specific problems, such as supporting citizen participation, coping with information uncertainties and quality variations or enhancing inter-organizational learning. | ||||
| Address | Institute for Information Systems, University of Siegen, Germany; Research School Business and Economics, University of Siegen, Germany | ||||
| Corporate Author | Thesis | ||||
| Publisher | Information Systems for Crisis Response and Management, ISCRAM | Place of Publication | Lisbon | Editor | M.A. Santos, L. Sousa, E. Portela |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9789724922478 | Medium | |
| Track | Social Media and Collaborative Systems | Expedition | Conference | 8th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1090 | |||
| Share this record to Facebook | |||||
| Author |
Tracey L. O'Sullivan; Wayne Corneil; Craig E. Kuziemsky; Daniel E. Lane | ||||
| Title | Citizen participation in the specification and mapping of potential disaster assets | Type | Conference Article | ||
| Year | 2013 | Publication | ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2013 |
| Volume | Issue | Pages | 890-895 | ||
| Keywords | Disaster prevention; Disasters; Information systems; Innovation; Asset-mapping; Collaboration; Empowerment; Engagement; Resilience; Mapping | ||||
| Abstract | Asset-mapping is a strategy used in disaster preparedness planning, however participation is typically limited to a small number of organizations with specific expertise related to disaster response. Broader strategies are needed to ensure identification of assets is comprehensive and to stimulate innovative thinking about which attributes of a community are potential assets for response and recovery. As part of The EnRiCH Project intervention, asset-mapping was used as a collaborative activity to promote identification of a broad range of assets which could be used to enhance resilience and promote preparedness among high risk populations. In this paper we present a study (in progress) which explores innovation and empowerment among a collaborative community group in Canada. Qualitative content analysis was used to analyze focus group transcripts from 2 sessions where the participants (n=18) learned how to use google docs and create a database of community assets, while developing collaborative relationships. | ||||
| Address | Interdisciplinary School of Health Sciences, University of Ottawa, Canada; Institute of Population Health, University of Ottawa, Canada; Telfer School of Management, University of Ottawa, Canada | ||||
| Corporate Author | Thesis | ||||
| Publisher | Karlsruher Institut fur Technologie | Place of Publication | KIT; Baden-Baden | Editor | T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9783923704804 | Medium | |
| Track | Social Media | Expedition | Conference | 10th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 819 | |||
| Share this record to Facebook | |||||
| Author |
Valentin Barriere; Guillaume Jacquet | ||||
| Title | How does a Pre-Trained Transformer Integrate Contextual Keywords? Application to Humanitarian Computing | Type | Conference Article | ||
| Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
| Volume | Issue | Pages | 766-771 | ||
| Keywords | Transformers, Contextual keywords, Humanitarian Computing, Tweets analysis | ||||
| Abstract | In a classification task, dealing with text snippets and metadata usually requires to deal with multimodal approaches. When those metadata are textual, it is tempting to use them intrinsically with a pre-trained transformer, in order to leverage the semantic information encoded inside the model. This paper describes how to improve a humanitarian classification task by adding the crisis event type to each tweet to be classified. Based on additional experiments of the model weights and behavior, it identifies how the proposed neural network approach is partially over-fitting the particularities of the Crisis Benchmark, to better highlight how the model is still undoubtedly learning to use and take advantage of the metadata's textual semantics. | ||||
| Address | European Commission's Joint Research Center; European Commission's Joint Research Center | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
| Track | Social Media for Disaster Response and Resilience | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
| Notes | valbarrierepro@gmail.com | Approved | no | ||
| Call Number | ISCRAM @ idladmin @ | Serial | 2371 | ||
| Share this record to Facebook | |||||
| Author |
Valerio Lorini; Carlos Castillo; Francesco Dottori; Milan Kalas; Domenico Nappo; Peter Salamon | ||||
| Title | Integrating Social Media into a Pan-European Flood Awareness System: A Multilingual Approach | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages | |||
| Keywords | Social Media, Disaster Risk Management, Flood Risk | ||||
| Abstract | This paper describes a prototype system that integrates social media analysis into the European Flood Awareness System (EFAS). This integration allows the collection of social media data to be automatically triggered by flood risk warnings determined by a hydro-meteorological model. Then, we adopt a multi-lingual approach to find flood-related messages by employing two state-of-the-art methodologies: language-agnostic word embeddings and language-aligned word embeddings. Both approaches can be used to bootstrap a classifier of social media messages for a new language with little or no labeled data. Finally, we describe a method for selecting relevant and representative messages and displaying them back in the interface of EFAS. |
||||
| Address | European Commission, Joint Research Centre (JRC), Ispra, Italy;Universitat Pompeu Fabra, Barcelona, Spain;KAJO, Slovakia | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1854 | |||
| Share this record to Facebook | |||||
| Author |
Valerio Lorini; Carlos Castillo; Steve Peterson; Paola Rufolo; Hemant Purohit; Diego Pajarito; João Porto de Albuquerque; Cody Buntain | ||||
| Title | Social Media for Emergency Management: Opportunities and Challenges at the Intersection of Research and Practice | Type | Conference Article | ||
| Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
| Volume | Issue | Pages | 772-777 | ||
| Keywords | Crisis Informatics, Social Media, Workshop Report, Disaster Management | ||||
| Abstract | This paper summarizes key opportunities and challenges identified during the workshop “Social Media for Disaster Risk Management: Researchers Meet Practitioners” which took place online in November 2020. It constitutes a work-in-progress towards identifying new directions for research and development of systems that can better serve the information needs of emergency managers. Practitioners widely recognize the potential of accessing timely information from social media. Nevertheless, the discussion outlined some critical challenges for improving its adoption during crises. In particular, validating such information and integrating it with authoritative information and into more traditional information systems for emergency managers requires further work, and the negative impacts of misinformation and disinformation need to be prevented. | ||||
| Address | European Commission, Joint Research Centre (JRC), Ispra, Italy; Universitat Pompeu Fabra, Barcelona, Spain; Community Emergency Response Team, Montgomery County, Maryland, USA; European Commission, Joint Research Centre, Ispra, Italy; George Mason Univers | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
| Track | Social Media for Disaster Response and Resilience | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
| Notes | valerio.lorini@ec.europa.eu | Approved | no | ||
| Call Number | ISCRAM @ idladmin @ | Serial | 2372 | ||
| Share this record to Facebook | |||||
| Author |
Valerio Lorini; Javier Rando; Diego Saez-Trumper; Carlos Castillo | ||||
| Title | Uneven Coverage of Natural Disasters in Wikipedia: The Case of Floods | Type | Conference Article | ||
| Year | 2020 | Publication | ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2020 |
| Volume | Issue | Pages | 688-703 | ||
| Keywords | Social Media, News Values, Wikipedia, Natural Disasters, Floods. | ||||
| Abstract | The usage of non-authoritative data for disaster management provides timely information that might not be available through other means. Wikipedia, a collaboratively-produced encyclopedia, includes in-depth information about many natural disasters, and its editors are particularly good at adding information in real-time as a crisis unfolds. In this study, we focus on the most comprehensive version of Wikipedia, the English one. Wikipedia offers good coverage of disasters, particularly those having a large number of fatalities. However, by performing automatic content analysis at a global scale, we also show how the coverage of floods in Wikipedia is skewed towards rich, English-speaking countries, in particular the US and Canada. We also note how coverage of floods in countries with the lowest income is substantially lower than the coverage of floods in middle-income countries. These results have implications for analysts and systems using Wikipedia as an information source about disasters. | ||||
| Address | European Commission, Joint Research Centre (JRC), Ispra, Italy Universitat Pompeu Fabra, Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain; Wikimedia Foundation; Universitat Pompeu Fabra, Barcelona, Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-27-63 | ISBN | 2411-3449 | Medium | |
| Track | Social Media for Disaster Response and Resilie | Expedition | Conference | 17th International Conference on Information Systems for Crisis Response and Management | |
| Notes | valerio.lorini@ec.europa.eu | Approved | no | ||
| Call Number | Serial | 2264 | |||
| Share this record to Facebook | |||||
| Author |
Venkata Kishore Neppalli; Cornelia Caragea; Doina Caragea | ||||
| Title | Deep Neural Networks versus Naive Bayes Classifiers for Identifying Informative Tweets during Disasters | Type | Conference Article | ||
| Year | 2018 | Publication | ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2018 |
| Volume | Issue | Pages | 677-686 | ||
| Keywords | deep neural networks, naive bayes classifiers, handcrafted features | ||||
| Abstract | In this paper, we focus on understanding the effectiveness of deep neural networks by comparison with the effectiveness of standard classifiers that use carefully engineered features. Specifically, we design various feature sets (based on tweet content, user details and polarity clues) and use these feature sets individually or in various combinations, with Naïve Bayes classifiers. Furthermore, we develop neural models based on Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) with handcrafted architectures. We compare the two types of approaches in the context of identifying informative tweets posted during disasters, and show that the deep neural networks, in particular the CNN networks, are more effective for the task considered. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Rochester Institute of Technology | Place of Publication | Rochester, NY (USA) | Editor | Kees Boersma; Brian Tomaszeski |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-0-692-12760-5 | Medium | |
| Track | Social Media Studies CO - | Expedition | Conference | ||
| Notes | Approved | no | |||
| Call Number | Serial | 2141 | |||
| Share this record to Facebook | |||||
| Author |
Venkata Kishore Neppalli; Murilo Cerqueira Medeiros; Cornelia Caragea; Doina Caragea; Andrea Tapia; Shane Halse | ||||
| Title | Retweetability Analysis and Prediction during Hurricane Sandy | Type | Conference Article | ||
| Year | 2016 | Publication | ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2016 |
| Volume | Issue | Pages | |||
| Keywords | Twitter; Retweetability Analysis; Retweetability Prediction; Hurricane Sandy; Disaster Events | ||||
| Abstract | Twitter is a very important source for obtaining information, especially during events such as natural disasters. Users can spread information in Twitter either by crafting new posts, which are called ?tweets,? or by using retweet mechanism to re-post the previously created tweets. During natural disasters, identifying how likely a tweet is to be highly retweeted is very important since it can help promote the spread of good information in a network such as Twitter, as well as it can help stop the spread of misinformation, when corroborated with approaches that identify trustworthy information or misinformation, respectively. In this paper, we present an analysis on retweeted tweets to determine several aspects affecting retweetability. We then extract features from tweets? content and user account information and perform experiments to develop models that automatically predict the retweetability of a tweet in the context of the Hurricane Sandy. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Federal University of Rio de Janeiro | Place of Publication | Rio de Janeiro, Brasil | Editor | A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3388 | ISBN | 978-84-608-7984-9 | Medium | |
| Track | Social Media Studies | Expedition | Conference | 13th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 1389 | |||
| Share this record to Facebook | |||||
| Author |
Wang, D.; Kogan, M. | ||||
| Title | Resonance+: Augmenting Collective Attention to Find Information on Public Cognition and Perception of Risk | Type | Conference Article | ||
| Year | 2023 | Publication | Proceedings of the 20th International ISCRAM Conference | Abbreviated Journal | Iscram 2023 |
| Volume | Issue | Pages | 487-500 | ||
| Keywords | Crisis Informatics; Social Media Data; Word Embedding; Cognitive Process; Protective Action Decision Model | ||||
| Abstract | Microblogging platforms have been increasingly used by the public and crisis managers in crisis. The increasing volume of data has made such platforms more difficult for officials to find on-the-ground information and understand the public’s perception of the evolving risks. The crisis informatics literature has proposed various technological solutions to find relevant information from social media. However, the cognitive processes of the affected population and their subsequent responses, such as perceptions, emotional and behavioral responses, are still under-examined at scale. Yet, such information is important for gauging public perception of risks, an important task for PIOs and emergency managers. In this work, we leverage the noise-cutting power of collective attention and take cues from the Protective Action Decision Model, to propose a method that estimates shifts in collective attention with a special focus on the cognitive processes of those affected and their subsequent responses. | ||||
| Address | University of Utah, School of Computing; University of Utah, School of Computing | ||||
| Corporate Author | Thesis | ||||
| Publisher | University of Nebraska at Omaha | Place of Publication | Omaha, USA | Editor | Jaziar Radianti; Ioannis Dokas; Nicolas Lalone; Deepak Khazanchi |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Hosssein Baharmand | Series Title | Abbreviated Series Title | ||
| Series Volume | Series Issue | Edition | 1 | ||
| ISSN | 2411-3387 | ISBN | 979-8-218-21749-5 | Medium | |
| Track | Social Media for Crisis Management | Expedition | Conference | ||
| Notes | http://dx.doi.org/10.59297/IMVX7820 | Approved | no | ||
| Call Number | ISCRAM @ idladmin @ | Serial | 2542 | ||
| Share this record to Facebook | |||||
| Author |
William R. Smith; Keri K. Stephens; Brett Robertson; Jing Li; Dhiraj Murthy | ||||
| Title | Social Media in Citizen-Led Disaster Response: Rescuer Roles, Coordination Challenges, and Untapped Potential | Type | Conference Article | ||
| Year | 2018 | Publication | ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2018 |
| Volume | Issue | Pages | 639-648 | ||
| Keywords | Crisis communication, social media, emergent groups, mobile technology, emergency management | ||||
| Abstract | Widespread disasters can overload official agencies' capacity to provide assistance, and often citizen-led groups emerge to assist with disaster response. As social media platforms have expanded, emergent rescue groups have many ways to harness network and mobile tools to coordinate actions and help fellow citizens. This study used semi-structured interviews and photo elicitation techniques to better understand how wide-scale rescues occurred during the 2017 Hurricane Harvey flooding in the Greater Houston, Texas USA area. We found that citizens used diverse apps and social media-related platforms during these rescues and that they played one of three roles: rescuer, dispatcher, or information compiler. The key social media coordination challenges these rescuers faced were incomplete feedback loops, unclear prioritization, and communication overload. This work-in-progress paper contributes to the field of crisis and disaster response research by sharing the nuances in how citizens use social media to respond to calls for help from flooding victims. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Rochester Institute of Technology | Place of Publication | Rochester, NY (USA) | Editor | Kees Boersma; Brian Tomaszeski |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-0-692-12760-5 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 2138 | |||
| Share this record to Facebook | |||||
| Author |
Xiao Li; Julia Kotlarsky; Michael D. Myers | ||||
| Title | Crowdsourcing and the COVID-19 Response in China: An Actor-Network Perspective | Type | Conference Article | ||
| Year | 2023 | Publication | Proceedings of the ISCRAM Asia Pacific Conference 2022 | Abbreviated Journal | Proc. ISCRAM AP 2022 |
| Volume | Issue | Pages | 240-246 | ||
| Keywords | Disaster; Crowdsourcing; Actor-Network; Social Media | ||||
| Abstract | Crowdsourcing, serving as a distributed problem-solving and production model, can help in the response to a disaster. The current literature focuses on the flow of crowdsourced information, but the question of how crowdsourcing contributes to physical disaster workflows remains to be addressed. Based on a case study of China’s response to COVID-19, this research aims to explore the role of crowdsourcing stakeholders and how they acted to respond to the outbreak. Actor network theory is applied as the lens to elucidate the roles of different heterogeneous actors. The preliminary results indicate that socio-technical actors activated, absorbed, associated, and aligned with each other to combat the pandemic. We suggest ways to augment the actor network to address potential future outbreaks. | ||||
| Address | University of Auckland; University of Auckland; University of Auckland | ||||
| Corporate Author | Thesis | ||||
| Publisher | Massey Unversity | Place of Publication | Palmerston North, New Zealand | Editor | Thomas J. Huggins, V.L. |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-0-473-66845-7 | Medium | |
| Track | Social Media for Disaster Response | Expedition | Conference | ||
| Notes | Approved | no | |||
| Call Number | ISCRAM @ idladmin @ | Serial | 2497 | ||
| Share this record to Facebook | |||||
| Author |
Xukun Li; Doina Caragea | ||||
| Title | Improving Disaster-related Tweet Classification with a Multimodal Approach | Type | Conference Article | ||
| Year | 2020 | Publication | ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2020 |
| Volume | Issue | Pages | 893-902 | ||
| Keywords | Multimodal Model; Tweet Classification; Deep Learning | ||||
| Abstract | Social media data analysis is important for disaster management. Lots of prior studies have focused on classifying a tweet based on its text or based on its images, independently, even if the tweet contains both text and images. Under the assumptions that text and images may contain complementary information, it is of interest to construct classifiers that make use of both modalities of the tweet. Towards this goal, we propose a multimodal classification model which aggregates text and image information. Our study aims to provide insights into the benefits obtained by combining text and images, and to understand what type of modality is more informative with respect to disaster tweet classification. Experimental results show that both text and image classification can be improved by the multimodal approach. | ||||
| Address | Department of Computer Science, Kansas State University; Department of Computer Science, Kansas State University | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-27-79 | ISBN | 2411-3465 | Medium | |
| Track | Social Media for Disaster Response and Resilie | Expedition | Conference | 17th International Conference on Information Systems for Crisis Response and Management | |
| Notes | xukun@ksu.edu | Approved | no | ||
| Call Number | Serial | 2280 | |||
| Share this record to Facebook | |||||
| Author |
Xukun Li; Doina Caragea; Cornelia Caragea; Muhammad Imran; Ferda Ofli | ||||
| Title | Identifying Disaster Damage Images Using a Domain Adaptation Approach | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages | |||
| Keywords | image classification, disaster damage, domain adaptation, domain adversarial neural networks. | ||||
| Abstract | Approaches for effectively filtering useful situational awareness information posted by eyewitnesses of disasters, in real time, are greatly needed. While many studies have focused on filtering textual information, the research on filtering disaster images is more limited. In particular, there are no studies on the applicability of domain adaptation to filter images from an emergent target disaster, when no labeled data is available for the target disaster. To fill in this gap, we propose to apply a domain adaptation approach, called domain adversarial neural networks (DANN), to the task of identifying images that show damage. The DANN approach has VGG-19 as its backbone, and uses the adversarial training to find a transformation that makes the source and target data indistinguishable. Experimental results on several pairs of disasters suggest that the DANN model generally gives similar or better results as compared to the VGG-19 model fine-tuned on the source labeled data. |
||||
| Address | Department of Computer Science, Kansas State University, United States of America;Department of Computer Science, University of Illinois at Chicago, United States of America;Qatar Computing Research Institute, Hamad Bin Khalifa University, Qatar | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1853 | |||
| Share this record to Facebook | |||||
| Author |
Yajie Li; Amanda Lee Hughes; Peter D. Howe | ||||
| Title | Communicating Crisis with Persuasion: Examining Official Twitter Messages on Heat Hazards | Type | Conference Article | ||
| Year | 2018 | Publication | ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2018 |
| Volume | Issue | Pages | 469-479 | ||
| Keywords | Persuasion, crisis communication, susceptibility, social media, heat hazards. | ||||
| Abstract | Official crisis messages need to be persuasive to promote appropriate public responses. However, little research has examined the content of crisis messages from a persuasion perspective, especially for natural hazards. This study deductively identifies five persuasive message factors (PMFs) applicable to natural hazards, including two under-examined health-related PMFs: health risk susceptibility and health impact. Using 2016 heat hazards as a case study, this paper content-analyzes heat-related Twitter messages (N=904) posted by eighteen U.S. National Weather Service Weather Forecast Offices according to the five PMFs. We find that the use of descriptions of hazard intensity is disproportionately high, with a lack of use of other PMFs. We also describe different types of statements used to signal the two health-related PMFs. We conclude with implications and recommendations relevant to practitioners and researchers in social media crisis communication. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | Rochester Institute of Technology | Place of Publication | Rochester, NY (USA) | Editor | Kees Boersma; Brian Tomaszeski |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-0-692-12760-5 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 2124 | |||
| Share this record to Facebook | |||||
| Author |
Yan Wang; Qi Wang; John Taylor | ||||
| Title | Loss of Resilience in Human Mobility across Severe Tropical Cyclones of Different Magnitudes | Type | Conference Article | ||
| Year | 2021 | Publication | ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | Iscram 2021 |
| Volume | Issue | Pages | 755-765 | ||
| Keywords | Disaster Resilience, Geo-social networking, Human mobility, Tropical Cyclones | ||||
| Abstract | Severe tropical cyclones impose threats on highly populated coastal urban areas, thereby, understanding and predicting human movements plays a critical role in evaluating disaster resilience of human society. However, limited research has focused on tropical cyclones and their influence on human mobility resilience. This preliminary study examined the strength and duration of human mobility perturbation across five significant tropical storms and their affected eight urban areas using Twitter data. The results suggest that tropical cyclones can significantly perturb human movements by changing travel frequencies and displacement probability distributions. While the power-law still best described the pattern of human movements, the changes in the radii of gyration were significant and resulted in perturbation and loss of resilience in human mobility. The findings deepen the understanding about human-environment interactions under extreme events, improve our ability to predict human movements using social media data, and help policymakers improve disaster evacuation and response. | ||||
| Address | University of Florida; Northeastern University; Georgia Institute of Technology | ||||
| Corporate Author | Thesis | ||||
| Publisher | Virginia Tech | Place of Publication | Blacksburg, VA (USA) | Editor | Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 978-1-949373-61-5 | ISBN | Medium | ||
| Track | Social Media for Disaster Response and Resilience | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
| Notes | yanw@ufl.edu | Approved | no | ||
| Call Number | ISCRAM @ idladmin @ | Serial | 2370 | ||
| Share this record to Facebook | |||||
| Author |
Yang Ishigaki; Yoshinori Matsumoto; Yutaka Matsuno; Kenji Tanaka | ||||
| Title | Participatory Radiation Information Monitoring with SNS after Fukushima | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
| Volume | Issue | Pages | |||
| Keywords | Facebook; Nuclear Disaster; Open Source Hardware; Social Inclusion | ||||
| Abstract | We developed a series of inexpensive but accurate mobile radiation detectors, which we named Pocket Geiger (POKEGA), to address the urgent desire of ordinary people to measure and share radiation levels in their milieus and to discuss the results of the Nuclear Disaster in Fukushima, Japan. This action research reports on a new style of pragmatic model of radiation monitoring, which employs the features of Participatory Design and Participatory Sensing and adopts modern communication platforms such as crowd-funding, open source development, and Facebook. This paper proposes an interaction model between the project management body, and other inclusive corroborators, e.g., ordinary users and experts, and focuses on three development phases of the project: start-up phase, evaluation phase, and operation phase. This paper also considers a reliability assurance model on disaster information sharing between the citizen layer and the official layer by data sharing and discussion activities in the POKEGA community. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1243 | |||
| Share this record to Facebook | |||||
| Author |
Yang Zhang; William Drake; Yuhong Li; Christopher Zobel; Margaret Cowell | ||||
| Title | Fostering Community Resilience through Adaptive Learning in a Social Media Age: Municipal Twitter Use in New Jersey following Hurricane Sandy | Type | Conference Article | ||
| Year | 2015 | Publication | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2015 |
| Volume | Issue | Pages | |||
| Keywords | Adaptive learning; disaster resilience; Hurricane Sandy; social media; Twitter | ||||
| Abstract | Adaptive learning capacity is a critical component of community resilience that describes the ability of a community to effectively gauge its vulnerability to the external environment and to make appropriate changes to its coping strategies. Traditionally, the relationship between government and community learning was framed within a deterministic paradigm. Learning outcomes were understood to result from the activities of central actors (i.e., government) and flow passively into the community. The emergence of social media is fundamentally changing the ways organizations and individuals collect and share information. Despite its growing acceptance, it remains to be determined how this shift in communication will ultimately affect community adaptive learning, and therefore, community resilience. This paper presents the initial results of a mixed-methods research effort that examined the use of Twitter in local municipalities from Monmouth County, NJ after Hurricane Sandy. Using a conceptual model of organizational learning, we examine the learning outcomes following the Hurricane Sandy experience. | ||||
| Address | |||||
| Corporate Author | Thesis | ||||
| Publisher | University of Agder (UiA) | Place of Publication | Kristiansand, Norway | Editor | L. Palen; M. Buscher; T. Comes; A. Hughes |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9788271177881 | Medium | |
| Track | Social Media Studies | Expedition | Conference | ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | yes | |||
| Call Number | Serial | 1236 | |||
| Share this record to Facebook | |||||
| Author |
Yingjie Li; Seoyeon Park; Cornelia Caragea; Doina Caragea; Andrea Tapia | ||||
| Title | Sympathy Detection in Disaster Twitter Data | Type | Conference Article | ||
| Year | 2019 | Publication | Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management | Abbreviated Journal | Iscram 2019 |
| Volume | Issue | Pages | |||
| Keywords | Word Embedding, Deep Learning, Machine Learning, Sympathy Tweets Detection | ||||
| Abstract | Nowadays, micro-blogging sites such as Twitter have become powerful tools for communicating with others in various situations. Especially in disaster events, these sites can be the best platforms for seeking or providing social support, of which informational support and emotional support are the most important types. Sympathy, a sub-type of emotional support, is an expression of one?s compassion or sorrow for a difficult situation that another person is facing. Providing sympathy to people affected by a disaster can help change people?s emotional states from negative to positive emotions, and hence, help them feel better. Moreover, detecting sympathy contents in Twitter can potentially be used for finding candidate donors since the emotion ?sympathy? is closely related to people who may be willing to donate. Thus, in this paper, as a starting point, we focus on detecting sympathy-related tweets. We address this task using Convolutional Neural Networks (CNNs) with refined word embeddings. Specifically, we propose a refined word embedding technique in terms of various pre-trained word vector models and show great performance of CNNs that use these refined embeddings in the sympathy tweet classification task. We also report experimental results showing that the CNNs with the refined word embeddings outperform not only traditional machine learning techniques, such as Naïve Bayes, Support Vector Machines and AdaBoost with conventional feature sets as bags of words, but also Long Short-Term Memory Networks. |
||||
| Address | University of Illinois at Chicago, United States of America;Kansas State University, United States of America;Pennsylvania State University, United States of America | ||||
| Corporate Author | Thesis | ||||
| Publisher | Iscram | Place of Publication | Valencia, Spain | Editor | Franco, Z.; González, J.J.; Canós, J.H. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 978-84-09-10498-7 | Medium | |
| Track | T8- Social Media in Crises and Conflicts | Expedition | Conference | 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) | |
| Notes | Approved | no | |||
| Call Number | Serial | 1899 | |||
| Share this record to Facebook | |||||
| Author |
Yongzhong Sha; Jinsong Yan; Guoray Cai | ||||
| Title | Detecting public sentiment over PM2.5 pollution hazards through analysis of Chinese microblog | Type | Conference Article | ||
| Year | 2014 | Publication | ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management | Abbreviated Journal | ISCRAM 2014 |
| Volume | Issue | Pages | 722-726 | ||
| Keywords | Air pollution; Information systems; Time series analysis; Crisis; Pm2.5; Public opinions; Sentiment analysis; Social media analysis; Social aspects | ||||
| Abstract | Decision-making in crisis management can benefit from routine monitoring of the (social) media to discover the mass opinion on highly sensitive crisis events. We present an experiment that analyzes Chinese microblog data (extracted from Weibo.cn) to measure sentiment strength and its change in relation to the recent PM 2.5 air pollution events. The data were analyzed using SentiStrength algorithm together with a special sentiment words dictionary tailored and refined for Chinese language. The results of time series analysis on detected sentiment strength showed that less than one percent of the posts are strong-positive or strong negative. Weekly sentiment strength measures show symmetric changes in positive and negative strength, but overall trend moved towards more positive opinions. Special attention was given to sharp bursts of sentiment strength that coincide temporally with the occurrence of extreme social events. These findings suggest that sentiment strength analysis may generate useful alert and awareness of pending extreme social events. | ||||
| Address | Lanzhou University, Gansu, China; Penn State University, University Park, PA, United States | ||||
| Corporate Author | Thesis | ||||
| Publisher | The Pennsylvania State University | Place of Publication | University Park, PA | Editor | S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 2411-3387 | ISBN | 9780692211946 | Medium | |
| Track | Social Media in Crisis Response and Management | Expedition | Conference | 11th International ISCRAM Conference on Information Systems for Crisis Response and Management | |
| Notes | Approved | no | |||
| Call Number | Serial | 939 | |||
| Share this record to Facebook | |||||