| Records |
| Author |
Shane Errol Halse; Aurélie Montarnal; Andrea Tapia; Frederick Benaben |
| Title |
Bad Weather Coming: Linking social media and weather sensor data |
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 |
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Issue |
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Pages |
507-515 |
| Keywords |
Twitter; weather; sensor data; social media |
| Abstract |
In this paper we leverage the power of citizen supplied data. We examined how both physical weather sensor data (obtained from the weather underground API) and social media data (obtained from Twitter) can serve to improve local community awareness during a severe weather event. A local tornado warning was selected due to its small scale and isolated geographic area, and only Twitter data found from within this geo-locational area was used. Our results indicate that during a severe weather event, an increase in weather activity obtained from the local weather sensors does correlate with an increase in local social media usage. The data found on social media also contains additional information from, and about the community of interest during the event. While this study focuses on a small scale event, it provides the groundwork for use during a much larger weather event. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
Medium |
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| Track |
Social Media Studies |
Expedition |
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Conference  |
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management |
| Notes |
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Approved |
no |
| Call Number |
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Serial |
2127 |
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| Author |
Shane Halse; Jomara Binda; Samantha Weirman |
| Title |
It's what's outside that counts: Finding credibility metrics through non-message related Twitter features |
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 |
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Issue |
|
Pages |
516-528 |
| Keywords |
Twitter; social media; trust |
| Abstract |
Social media data, such as Twitter, enables crisis response personnel and civilians to share information during a crisis situation. However, a lack of information gatekeeping processes also translates into concerns about both content and source credibility. This research aims to identify Twitter metrics which could assist with the latter. A 2 (average number of hashtags used) x 2 (ratio of tweets/retweets posted) x 2 (ratio of follower/followee) between-subjects experiment was conducted to evaluate the level of influence of Twitter broker metrics on behavioral intention and the perception of source credibility. The findings indicate that follower/followee ratio in conjunction with hashtag usage approached a significant effect on perceived source credibility. In addition, both Twitter awareness metrics and dispositional trust played an important role in determining behavioral intentions and perceived source credibility. Implications and limitations are also discussed. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
Medium |
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| Track |
Social Media Studies |
Expedition |
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Conference |
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management |
| Notes |
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Approved |
no |
| Call Number |
|
Serial |
2128 |
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| Author |
Takuya Oki |
| Title |
Possibility of Using Tweets to Detect Crowd Congestion: A Case Study Using Tweets just before/after the Great East Japan Earthquake |
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 |
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Issue |
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Pages |
584-596 |
| Keywords |
Twitter, crowd congestion, time-series analysis, linguistic expression, disaster mitigation. |
| Abstract |
During large earthquakes, it is critical to safely guide evacuation efforts and to prevent accidents caused by congestion. In this paper, we focus on detecting the degree of crowd congestion following an earthquake based on information posted to Social Networking Services (SNSs). This research uses text data posted to Twitter just before/after the occurrence of the Great East Japan Earthquake (11 March 2011 at 02:46 PM JST). First, we extract co-occurring place names, proper nouns, and time-series information from tweets about congestion in the Tokyo metropolitan area (TMA). Next, using these extracted data, we analyze the frequency and spatiotemporal characteristics of these tweets. Finally, we identify expressions that describe the degree of crowd congestion and discuss methods to quantify these expressions based on a questionnaire survey and tweets that contain a photograph. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
Medium |
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| Track |
Social Media Studies |
Expedition |
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Conference |
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management |
| Notes |
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Approved |
no |
| Call Number |
|
Serial |
2133 |
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| Author |
Leon Derczynski; Kenny Meesters; Kalina Bontcheva; Diana Maynard |
| Title |
Helping Crisis Responders Find the Informative Needle in the Tweet Haystack |
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 |
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Issue |
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Pages |
649-662 |
| Keywords |
informativeness, twitter, social media, actionability, information filtering |
| Abstract |
Crisis responders are increasingly using social media, data and other digital sources of information to build a situational understanding of a crisis situation in order to design an effective response. However with the increased availability of such data, the challenge of identifying relevant information from it also increases. This paper presents a successful automatic approach to handling this problem. Messages are filtered for informativeness based on a definition of the concept drawn from prior research and crisis response experts. Informative messages are tagged for actionable data – for example, people in need, threats to rescue efforts, changes in environment, and so on. In all, eight categories of actionability are identified. The two components – informativeness and actionability classification – are packaged together as an openly-available tool called Emina (Emergent Informativeness and Actionability). |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
Medium |
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| Track |
Social Media Studies |
Expedition |
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Conference |
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management |
| Notes |
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Approved |
no |
| Call Number |
|
Serial |
2139 |
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| Author |
Songhui Yue; Jyothsna Kondari; Aibek Musaev; Songqing Yue; Randy Smith |
| Title |
Using Twitter Data to Determine Hurricane Category: An Experiment |
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 |
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Issue |
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Pages |
718-726 |
| Keywords |
Social Media Data, Hurricane Category, Twitter, Prediction |
| Abstract |
Social media posts contain an abundant amount of information about public opinion on major events, especially natural disasters such as hurricanes. Posts related to an event, are usually published by the users who live near the place of the event at the time of the event. Special correlation between the social media data and the events can be obtained using data mining approaches. This paper presents research work to find the mappings between social media data and the severity level of a disaster. Specifically, we have investigated the Twitter data posted during hurricanes Harvey and Irma, and attempted to find the correlation between the Twitter data of a specific area and the hurricane level in that area. Our experimental results indicate a positive correlation between them. We also present a method to predict the hurricane category for a specific area using relevant Twitter data. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
| Language |
English |
Summary Language |
English |
Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
Medium |
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| 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 |
2145 |
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