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Analyzing Temporal Dynamics in Twitter Profiles for Personalized Recommendations in the Social Web
Published on Jul 19, 20114005 Views
Social Web describes a new culture of participation on the Web where more and more people actively participate in publishing and organizing Web content. As part of this cul- ture, people leave a va
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Chapter list
Analyzing Temporal Dynamics inTwitter Profiles for Personalized Recommendations on the Social Web00:00
The Social Web00:15
What we do: Science and Engineering for the Personal Web00:43
What we do in this paper02:04
Research Questions03:04
Dataset03:29
How do topics evolve over time? (1)03:57
Representing a topic: via entities (and hashtags)04:06
How do topics evolve over time? (2)04:37
Popularity of related entities over time (1)05:17
Popularity of related entities over time (2)05:45
How do topics evolve over time? -> Observations06:10
How do the interests of individual users into a topic change over time?06:38
When do users become interested?06:51
Users’ interests over time (1)07:40
Users’ interests over time (2)08:13
Users’ interests over time (3)08:37
How do the interests of individual users into a topic change over time? -> Observations09:07
Can we exploit Twitter-based profiles for personalizing users’ Social Web experience?09:53
Twitter-based user profiles10:07
Twitter-based Profiles for Personalization11:04
Which user modeling strategy is best for computing personalized recommendations?11:39
"Best" user modeling strategy varies for different types of user12:00
Impact of profile size on recommendation quality12:22
Conclusions and Future Work12:42
Thank you!14:17