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Author | Usman Anjum; Vladimir Zadorozhny; Prashant Krishnamurthy | ||||
Title | TBAM: Towards An Agent-Based Model to Enrich Twitter Data | 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 | 146-158 | ||
Keywords | Agent-Based Model, Twitter, Modeling and Simulation, Event Detection | ||||
Abstract | Twitter is widely being used by researchers to understand human behavior, e.g. how people behave when an event occurs and how it changes their microblogging pattern. The changing microblogging behavior can have an important application in the form of detecting events. However, the Twitter data that is available has limitations in it has incomplete and noisy information and has irregular samples. In this paper we create a model, calledTwitter Behavior Agent-Based Model (TBAM)to simulate Twitter pattern and behavior using Agent-Based Modeling(ABM). The generated data can be used in place or to complement the real-world data and improve the accuracy of event detection. We confirm the validity of our model by comparing it with real data collected from Twitter | ||||
Address | University of Pittsburgh; University of Pittsburgh; University of Pittsburgh | ||||
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 | Analytical Modeling and Simulation | Expedition | Conference | 18th International Conference on Information Systems for Crisis Response and Management | |
Notes | usa3@pitt.edu | Approved | no | ||
Call Number | ISCRAM @ idladmin @ | Serial | 2321 | ||
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