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| Content Provider | ACM Digital Library |
|---|---|
| Author | Meier, Florian Elsweiler, David |
| Abstract | Social Media (SM) has become a valuable information source to many in diverse situations. In IR, research has focused on real-time aspects and as such little is known about how long SM content is of value to users, if and how often it is re-accessed, the strategies people employ to re-access and if difficulties are experienced while doing so. We present results from a 5 month-long naturalistic, log-based study of user interaction with Twitter, which suggest re-finding to be a regular activity and that Tweets can offer utility for longer than one might think. We shed light on re-finding strategies revealing that remembered people are used as a stepping stone to Tweets rather than searching for content directly. Bookmarking strategies reported in the literature are used infrequently as a means to re-access. Finally, we show that by using statistical modelling it is possible to predict if a Tweet has future utility and is likely to be re-found. Our findings have implications for the design of social media search systems and interfaces, in particular for Twitter, to better support users re-find previously seen content. |
| Starting Page | 355 |
| Ending Page | 364 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450340694 |
| DOI | 10.1145/2911451.2911524 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-07-07 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Clickstream analysis Twitter Re-finding |
| Content Type | Text |
| Resource Type | Article |
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