SentiBubbles: Topic Modeling and Sentiment Visualization of Entity-centric Tweets
Jo\~ao Oliveira, Mike Pinto, Pedro Saleiro, Jorge Teixeira
TL;DR
This paper introduces SentiBubbles, a method for aggregating and visualizing tweets centered on entities, using topic modeling and sentiment analysis to reveal public reactions to current events.
Contribution
It presents a novel approach combining entity-centric tweet aggregation with topic modeling and sentiment visualization for real-time event analysis.
Findings
Effective visualization of entity-based tweet sentiments
Enhanced understanding of public reactions to news events
Real-time insights into trending topics and sentiments
Abstract
Social Media users tend to mention entities when reacting to news events. The main purpose of this work is to create entity-centric aggregations of tweets on a daily basis. By applying topic modeling and sentiment analysis, we create data visualization insights about current events and people reactions to those events from an entity-centric perspective.
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Taxonomy
TopicsSentiment Analysis and Opinion Mining · Advanced Text Analysis Techniques · Complex Network Analysis Techniques