TwitInfo: Aggregating and Visualizing Microblogs for Event Exploration
Microblogs are a tremendous repository of user-generated content about world events. However, for people trying to understand events by querying services like Twitter, a chronological log of posts makes it very difficult to get a detailed understanding of an event. In this paper, we present TwitInfo...
| Main Authors: | , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Association for Computing Machinery (ACM)
2012
|
| Online Access: | http://hdl.handle.net/1721.1/72370 https://orcid.org/0000-0002-7470-3265 https://orcid.org/0000-0002-0024-5847 https://orcid.org/0000-0002-0442-691X |
| _version_ | 1826198413182500864 |
|---|---|
| author | Marcus, Adam Bernstein, Michael S. Badar, Osama Karger, David R. Madden, Samuel R. Miller, Robert C. |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Marcus, Adam Bernstein, Michael S. Badar, Osama Karger, David R. Madden, Samuel R. Miller, Robert C. |
| author_sort | Marcus, Adam |
| collection | MIT |
| description | Microblogs are a tremendous repository of user-generated content about world events. However, for people trying to understand events by querying services like Twitter, a chronological log of posts makes it very difficult to get a detailed understanding of an event. In this paper, we present TwitInfo, a system for visualizing and summarizing events on Twitter. TwitInfo allows users to browse a large collection of tweets using a timeline-based display that highlights peaks of high tweet activity. A novel streaming algorithm automatically discovers these peaks and labels them meaningfully using text from the tweets. Users can drill down to subevents, and explore further via geolocation, sentiment, and popular URLs. We contribute a recall-normalized aggregate sentiment visualization to produce more honest sentiment overviews. An evaluation of the system revealed that users were able to reconstruct meaningful summaries of events in a small amount of time. An interview with a Pulitzer Prize-winning journalist suggested that the system would be especially useful for understanding a long-running event and for identifying eyewitnesses. Quantitatively, our system can identify 80-100% of manually labeled peaks, facilitating a relatively complete view of each event studied. |
| first_indexed | 2024-09-23T11:04:29Z |
| format | Article |
| id | mit-1721.1/72370 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:04:29Z |
| publishDate | 2012 |
| publisher | Association for Computing Machinery (ACM) |
| record_format | dspace |
| spelling | mit-1721.1/723702022-10-01T00:58:59Z TwitInfo: Aggregating and Visualizing Microblogs for Event Exploration Marcus, Adam Bernstein, Michael S. Badar, Osama Karger, David R. Madden, Samuel R. Miller, Robert C. Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Karger, David R. Marcus, Adam Bernstein, Michael S. Badar, Osama Karger, David R. Madden, Samuel R. Miller, Robert C. Microblogs are a tremendous repository of user-generated content about world events. However, for people trying to understand events by querying services like Twitter, a chronological log of posts makes it very difficult to get a detailed understanding of an event. In this paper, we present TwitInfo, a system for visualizing and summarizing events on Twitter. TwitInfo allows users to browse a large collection of tweets using a timeline-based display that highlights peaks of high tweet activity. A novel streaming algorithm automatically discovers these peaks and labels them meaningfully using text from the tweets. Users can drill down to subevents, and explore further via geolocation, sentiment, and popular URLs. We contribute a recall-normalized aggregate sentiment visualization to produce more honest sentiment overviews. An evaluation of the system revealed that users were able to reconstruct meaningful summaries of events in a small amount of time. An interview with a Pulitzer Prize-winning journalist suggested that the system would be especially useful for understanding a long-running event and for identifying eyewitnesses. Quantitatively, our system can identify 80-100% of manually labeled peaks, facilitating a relatively complete view of each event studied. 2012-08-28T15:56:10Z 2012-08-28T15:56:10Z 2011-05 Article http://purl.org/eprint/type/ConferencePaper 978-1-4503-0228-9 http://hdl.handle.net/1721.1/72370 Adam Marcus, Michael S. Bernstein, Osama Badar, David R. Karger, Samuel Madden, and Robert C. Miller. 2011. Twitinfo: aggregating and visualizing microblogs for event exploration. In Proceedings of the 2011 annual conference on Human factors in computing systems (CHI '11). ACM, New York, NY, USA, 227-236. https://orcid.org/0000-0002-7470-3265 https://orcid.org/0000-0002-0024-5847 https://orcid.org/0000-0002-0442-691X en_US http://dx.doi.org/10.1145/1978942.1978975 Proceedings of the 2011 Annual Conference on Human Factors in Computing Systems (CHI '11) Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Association for Computing Machinery (ACM) MIT web domain |
| spellingShingle | Marcus, Adam Bernstein, Michael S. Badar, Osama Karger, David R. Madden, Samuel R. Miller, Robert C. TwitInfo: Aggregating and Visualizing Microblogs for Event Exploration |
| title | TwitInfo: Aggregating and Visualizing Microblogs for Event Exploration |
| title_full | TwitInfo: Aggregating and Visualizing Microblogs for Event Exploration |
| title_fullStr | TwitInfo: Aggregating and Visualizing Microblogs for Event Exploration |
| title_full_unstemmed | TwitInfo: Aggregating and Visualizing Microblogs for Event Exploration |
| title_short | TwitInfo: Aggregating and Visualizing Microblogs for Event Exploration |
| title_sort | twitinfo aggregating and visualizing microblogs for event exploration |
| url | http://hdl.handle.net/1721.1/72370 https://orcid.org/0000-0002-7470-3265 https://orcid.org/0000-0002-0024-5847 https://orcid.org/0000-0002-0442-691X |
| work_keys_str_mv | AT marcusadam twitinfoaggregatingandvisualizingmicroblogsforeventexploration AT bernsteinmichaels twitinfoaggregatingandvisualizingmicroblogsforeventexploration AT badarosama twitinfoaggregatingandvisualizingmicroblogsforeventexploration AT kargerdavidr twitinfoaggregatingandvisualizingmicroblogsforeventexploration AT maddensamuelr twitinfoaggregatingandvisualizingmicroblogsforeventexploration AT millerrobertc twitinfoaggregatingandvisualizingmicroblogsforeventexploration |