Sentiment Analysis of Events in Social Media

The growing popularity of Online Social Networks has open new research directions and perspectives for content analysis, i.e., Network Analysis and Natural Language Processing. From the perspective of information spread, the Network Analysis community propose Event Detection. This approach focuses on the network features, without an in-depth analysis of the textual content, summarization being a preferred method. Natural Language Processing analyses only the textual content, not integrating the graph-based structure of the network. To address these limitations, we propose a method that bridges the two directions and integrates content-awareness into networkawareness. Our method uses event detection to extract topics of interest and then applies sentiment analysis on each event. The obtained results have high accuracy, proving that our method determines with high precision the overall sentiment of the detected events.