Tracking Sentiment by Time Series Analysis

Anastasia Giachanou, Fabio Crestani
2016 Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval - SIGIR '16  
In recent years social media have emerged as popular platforms for people to share their thoughts and opinions on all kind of topics. Tracking opinion over time is a powerful tool that can be used for sentiment prediction or to detect the possible reasons of a sentiment change. Understanding topic and sentiment evolution allows enterprises or government to capture negative sentiment and act promptly. In this study, we explore conventional time series analysis methods and their applicability on
more » ... r applicability on topic and sentiment trend analysis. We use data collected from Twitter that span over nine months. Finally, we study the usability of outliers detection and different measures such as sentiment velocity and acceleration on the task of sentiment tracking.
doi:10.1145/2911451.2914702 dblp:conf/sigir/GiachanouC16 fatcat:xbiukvhpuvbo3grqahrhbkzzci