CommentsRadar: Dive into Unique Data on All Comments on the Web
This work addresses the need for systematic analysis of online comments for researchers and analysts, but it is incremental as it builds on existing techniques like entity extraction and sentiment analysis.
The authors tackled the problem of analyzing user opinions across the web by introducing CommentsRadar, an entity-centric search engine that aggregates articles and comments, extracts named entities, links them to knowledge bases, and performs sentiment analysis to mine temporal trends and insights.
We introduce an entity-centric search engineCommentsRadarthatpairs entity queries with articles and user opinions covering a widerange of topics from top commented sites. The engine aggregatesarticles and comments for these articles, extracts named entities,links them together and with knowledge base entries, performssentiment analysis, and aggregates the results, aiming to mine fortemporal trends and other insights. In this work, we present thegeneral engine, discuss the models used for all steps of this pipeline,and introduce several case studies that discover important insightsfrom online commenting data.