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Deciding What to Display: Maximizing the Information Value of Social Media
- Source :
- Proceedings of the International AAAI Conference on Web and Social Media. 9:13-21
- Publication Year :
- 2021
- Publisher :
- Association for the Advancement of Artificial Intelligence (AAAI), 2021.
-
Abstract
- In information-rich environments, the competition for users' attention leads to a flood of content from which people often find hard to sort out the most relevant and useful pieces. Using Twitter as a case study, we applied an attention economy solution to generate the most informative tweets for its users. By considering the novelty and popularity of tweets as objective measures of their relevance and utility, we used the Huberman-Wu algorithm to automatically select the ones that will receive the most attention in the next time interval. Their predicted popularity was confirmed by using Twitter data collected for a period of 2 months.
- Subjects :
- Social and Information Networks (cs.SI)
FOS: Computer and information sciences
Computer Science - Computers and Society
Physics - Physics and Society
Computers and Society (cs.CY)
Computer Science - Human-Computer Interaction
FOS: Physical sciences
Computer Science - Social and Information Networks
Physics and Society (physics.soc-ph)
Human-Computer Interaction (cs.HC)
Subjects
Details
- ISSN :
- 23340770 and 21623449
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- Proceedings of the International AAAI Conference on Web and Social Media
- Accession number :
- edsair.doi.dedup.....d3cf5aa2dd129c0c5ddea7590ccc1948