Name
Abstract | ||
|---|---|---|
Evolution of online social networks is driven by the need of their members to shareand consume content, resulting in a complex interplay between individual activity andattention received from others. In a context of increasing information overload andlimited resources, discovering which are the most successful behavioral patterns toattract attention is very important. To shed light on the matter, we look into thepatterns of activity and popularity of users in the Yahoo Meme microblogging service.We observe that a combination of different type of social and content-producingactivity is necessary to attract attention and the efficiency of users, namely theaverage attention received per piece of content published, for many users has adefined trend in its temporal footprint. The analysis of the user time series ofefficiency shows different classes of users whose different activity patterns giveinsights on the type of behavior that pays off best in terms of attention gathering.In particular, sharing content with high spreading potential and then supporting theattention raised by it with social activity emerges as a frequent pattern for usersgaining efficiency over time. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1140/epjds30 | EPJ Data Sci. |
Keywords | Field | DocType |
online attention, microblogging, social networks, time series | Data science,Behavioral pattern,Information overload,Social media,Social network,Social activity,Computer science,Popularity,Microblogging | Journal |
Volume | Issue | ISSN |
3 | 1 | 2193-1127 |
Citations | PageRank | References |
4 | 0.40 | 34 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carmen Vaca Ruiz | 1 | 5 | 1.11 |
| Luca Maria Aiello | 2 | 713 | 44.77 |
| Alejandro Jaimes | 3 | 1461 | 104.52 |