Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media
Influence cascades are typically analyzed using a single metric approach, i.e., all influence is measured using one number. However, social influence is not monolithic; different users exercise different influences in different ways, and influence is correlated with the user and content-specific att...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
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Multidisciplinary Digital Publishing Institute
2022
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| Online Access: | https://hdl.handle.net/1721.1/131341.2 |
| _version_ | 1811078509112590336 |
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| author | Senevirathna, Chathurani Gunaratne, Chathika Rand, William Jayalath, Chathura Garibay, Ivan |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Senevirathna, Chathurani Gunaratne, Chathika Rand, William Jayalath, Chathura Garibay, Ivan |
| author_sort | Senevirathna, Chathurani |
| collection | MIT |
| description | Influence cascades are typically analyzed using a single metric approach, i.e., all influence is measured using one number. However, social influence is not monolithic; different users exercise different influences in different ways, and influence is correlated with the user and content-specific attributes. One such attribute could be whether the action is an initiation of a new post, a contribution to a post, or a sharing of an existing post. In this paper, we present a novel method for tracking these influence relationships over time, which we call influence cascades, and present a visualization technique to better understand these cascades. We investigate these influence patterns within and across online social media platforms using empirical data and comparing to a scale-free network as a null model. Our results show that characteristics of influence cascades and patterns of influence are, in fact, affected by the platform and the community of the users. |
| first_indexed | 2024-09-23T11:01:17Z |
| format | Article |
| id | mit-1721.1/131341.2 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T11:01:17Z |
| publishDate | 2022 |
| publisher | Multidisciplinary Digital Publishing Institute |
| record_format | dspace |
| spelling | mit-1721.1/131341.22022-07-20T19:38:44Z Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media Senevirathna, Chathurani Gunaratne, Chathika Rand, William Jayalath, Chathura Garibay, Ivan Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Influence cascades are typically analyzed using a single metric approach, i.e., all influence is measured using one number. However, social influence is not monolithic; different users exercise different influences in different ways, and influence is correlated with the user and content-specific attributes. One such attribute could be whether the action is an initiation of a new post, a contribution to a post, or a sharing of an existing post. In this paper, we present a novel method for tracking these influence relationships over time, which we call influence cascades, and present a visualization technique to better understand these cascades. We investigate these influence patterns within and across online social media platforms using empirical data and comparing to a scale-free network as a null model. Our results show that characteristics of influence cascades and patterns of influence are, in fact, affected by the platform and the community of the users. DARPA program grant (number HR001117S0018) 2022-07-20T19:38:42Z 2021-09-20T14:16:17Z 2022-07-20T19:38:42Z 2021-01-28 2021-02-05T14:10:35Z Article http://purl.org/eprint/type/JournalArticle 1099-4300 https://hdl.handle.net/1721.1/131341.2 Entropy 23 (2): 160 (2021) PUBLISHER_CC https://dx.doi.org/10.3390/e23020160 Entropy Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ application/octet-stream Multidisciplinary Digital Publishing Institute Multidisciplinary Digital Publishing Institute |
| spellingShingle | Senevirathna, Chathurani Gunaratne, Chathika Rand, William Jayalath, Chathura Garibay, Ivan Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media |
| title | Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media |
| title_full | Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media |
| title_fullStr | Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media |
| title_full_unstemmed | Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media |
| title_short | Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media |
| title_sort | influence cascades entropy based characterization of behavioral influence patterns in social media |
| url | https://hdl.handle.net/1721.1/131341.2 |
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