Tracking the Yak: An empirical study of Yik Yak
To investigate the effects of anonymity on user behavior, we conduct an empirical study of the new and controversial social app, Yik Yak. First, we examine how users use the platform, analyzing patterns in posting, popularity of yaks, and vocabulary. As a comparison, we look at posting patterns on T...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Association for the Advancement of Artificial Intelligence
2020
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| Online Access: | https://hdl.handle.net/1721.1/125823 |
| _version_ | 1826196785194860544 |
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| author | Saveski, Martin Chou, Sophie Beiying Roy, Deb K |
| author2 | Massachusetts Institute of Technology. Media Laboratory |
| author_facet | Massachusetts Institute of Technology. Media Laboratory Saveski, Martin Chou, Sophie Beiying Roy, Deb K |
| author_sort | Saveski, Martin |
| collection | MIT |
| description | To investigate the effects of anonymity on user behavior, we conduct an empirical study of the new and controversial social app, Yik Yak. First, we examine how users use the platform, analyzing patterns in posting, popularity of yaks, and vocabulary. As a comparison, we look at posting patterns on Twitter, which has similar limitations on lengths of posts, but is public and global rather than anonymous and local. Upon a sample of 2.9M posts (1.9M yaks and 1M geotagged tweets) from 20 locations across the USA, we find that interactions on Yik Yak are specific to its location limitations and reflect the schedules of its targeted demographic, college students. Second, we test two hypotheses related to anonymity and communication: (i) whether vulgarity usage is more likely to be acceptable, and (ii) whether unique topics emerge in conversations on Yik Yak. We find that posts on Yik Yak are only slightly more likely to contain vulgarities, and we do not find any significant bias in topic distributions on Yik Yak versus on Twitter; however, differences in vocabulary and most discriminative words used suggest the need for further analysis. |
| first_indexed | 2024-09-23T10:37:58Z |
| format | Article |
| id | mit-1721.1/125823 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T10:37:58Z |
| publishDate | 2020 |
| publisher | Association for the Advancement of Artificial Intelligence |
| record_format | dspace |
| spelling | mit-1721.1/1258232022-09-27T13:51:43Z Tracking the Yak: An empirical study of Yik Yak Saveski, Martin Chou, Sophie Beiying Roy, Deb K Massachusetts Institute of Technology. Media Laboratory To investigate the effects of anonymity on user behavior, we conduct an empirical study of the new and controversial social app, Yik Yak. First, we examine how users use the platform, analyzing patterns in posting, popularity of yaks, and vocabulary. As a comparison, we look at posting patterns on Twitter, which has similar limitations on lengths of posts, but is public and global rather than anonymous and local. Upon a sample of 2.9M posts (1.9M yaks and 1M geotagged tweets) from 20 locations across the USA, we find that interactions on Yik Yak are specific to its location limitations and reflect the schedules of its targeted demographic, college students. Second, we test two hypotheses related to anonymity and communication: (i) whether vulgarity usage is more likely to be acceptable, and (ii) whether unique topics emerge in conversations on Yik Yak. We find that posts on Yik Yak are only slightly more likely to contain vulgarities, and we do not find any significant bias in topic distributions on Yik Yak versus on Twitter; however, differences in vocabulary and most discriminative words used suggest the need for further analysis. 2020-06-16T18:56:00Z 2020-06-16T18:56:00Z 2016-03 2019-07-23T16:50:00Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/125823 Saveski, Martin et al. "Tracking the Yak: An Empirical Study of Yik Yak." International AAAI Conference on Web and Social Media, North America (2016). en https://www.aaai.org/ocs/index.php/ICWSM/ICWSM16/paper/view/13156 Tenth International AAAI Conference on Web and Social Media Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Association for the Advancement of Artificial Intelligence MIT web domain |
| spellingShingle | Saveski, Martin Chou, Sophie Beiying Roy, Deb K Tracking the Yak: An empirical study of Yik Yak |
| title | Tracking the Yak: An empirical study of Yik Yak |
| title_full | Tracking the Yak: An empirical study of Yik Yak |
| title_fullStr | Tracking the Yak: An empirical study of Yik Yak |
| title_full_unstemmed | Tracking the Yak: An empirical study of Yik Yak |
| title_short | Tracking the Yak: An empirical study of Yik Yak |
| title_sort | tracking the yak an empirical study of yik yak |
| url | https://hdl.handle.net/1721.1/125823 |
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