The RepLab summarization dataset contains companies data from the RepLab 2013 dataset. The collection comprises tweets about 31 entities from two domains: automotive and banking. As a result, our subset of RepLab 2013 comprises 71,303 English and Spanish tweets.
RepLab 2014 focuses on Reputation Monitoring on Twitter, targeting two new tasks: the categorization of messages with respect to standard reputation dimensions (Performance, Leadership, Innovation, etc.) and the characterization of Twitter profiles (author profiling) with respect to a certain activity domain.
We present a semi-automatic tool that assists experts in their daily work of monitoring the reputation of entities —companies, organizations or public figures- in Twitter.
The RepLab 2013 task is a (multilingual) evaluation exercise for Online Reputation Management systems. RepLab 2013 focused on monitoring the reputation of entities (companies, organizations, etc.) on Twitter. The monitoring task consists of filtering those that do refer to the entity, detecting topics (i.e., clustering tweets by subject) and ranking them based on the degree to which they signal reputation alerts.