What makes the city pulse
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Summary
This thesis addresses the problem of how to detect small scale unexpected events using UGC both in real-time and retrospectively and proposes a language-text joint modeling algorithm to cope with the large volume and unstructured nature of UGC.
- Type
- dissertation
- Published
- 2014-03-01
- Cited by
- 0
- References
- 69
- Access
- Open access
- OpenAlex
- https://openalex.org/W64451970
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:59654394
Keywords
Social media, Event (particle physics), Computer science, Metropolitan area, Set (abstract data type)
References
- An Empirical Study of Geographic User Activity Patterns in Foursquare
- Event Detection in Twitter
- Event Identification in Social Media
- Temporal and Information Flow Based Event Detection from Social Text Streams
- Event Detection and Tracking in Social Streams
- EURECOM @ MediaEval 2011 Social Event Detection Task
- Beyond Trending Topics: Real-World Event Identification on Twitter
- Twitter free Iran: An evaluation of Twitter's role in public diplomacy and information operations in Iran's 2009 election crisis
- The PageRank Citation Ranking : Bringing Order to the Web
- Towards automatic extraction of event and place semantics from flickr tags
- Who is tweeting on Twitter: human, bot, or cyborg?
- Event detection from flickr data through wavelet-based spatial analysis
- Why we blog
- Linear feature-based models for information retrieval
- A study of retrospective and on-line event detection
- Mining geographic knowledge using location aware topic model
- Discovery of unusual regional social activities using geo-tagged microblogs
- Content without context is meaningless
- TwitterStand: news in tweets
- Mining periodic behaviors for moving objects
Cited by
No citing papers recorded for this paper.
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