Event Identification in Social Networks
Fattane Zarrinkalam, Ebrahim Bagheri

TL;DR
This paper reviews current methods for detecting events in social networks, highlighting challenges posed by social media data and recent techniques that leverage abundant social information for improved event identification.
Contribution
It provides a comprehensive overview of state-of-the-art event detection techniques tailored for social network data, emphasizing recent advances addressing social media challenges.
Findings
Traditional methods are less effective on social media data.
Recent techniques exploit social network information for better detection.
The overview highlights ongoing research directions.
Abstract
Social networks enable users to freely communicate with each other and share their recent news, ongoing activities or views about different topics. As a result, they can be seen as a potentially viable source of information to understand the current emerging topics/events. The ability to model emerging topics is a substantial step to monitor and summarize the information originating from social sources. Applying traditional methods for event detection which are often proposed for processing large, formal and structured documents, are less effective, due to the short length, noisiness and informality of the social posts. Recent event detection techniques address these challenges by exploiting the opportunities behind abundant information available in social networks. This article provides an overview of the state of the art in event detection from social networks.
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Taxonomy
TopicsComplex Network Analysis Techniques · Web Data Mining and Analysis · Advanced Text Analysis Techniques
