Being on social media is akin to being constantly surrounded by other's perspectives, beliefs, and standards. We thought of the important of crowd sentiment in recent historical events and wondered why there was no simple platform for quickly gauging both positive and negative sentiment toward particular topics.
What it does
Hue mines Twitter and Reddit to determine crowd sentiment, both positive and negative, toward a particular topic. Using sentiment analysis, Hue aggregates similar opinions to determine the 5 most popular positive and negative notions towards the topic
How we built it
We used the Twitter and Reddit APIs to extract large sets of public messages for specific topics. We utilized NTLK, WordNet, and the semantic methods described in "Sentence Similarity Based on Semantic Nets and Corpus Statistics" Yuhua Li et al, 2006 to determine sentiment and semantic meaning of messages. On the front-end, we utilized Chartist.js and Bootstrap to render our data and views.
What's next for Hue
We would love to incorporate new data sources, such as Facebook and Tumblr, into our system. We would also love to do comparisons between different data sources to identify opinion differences among their different user bases. Furthermore, we would like to compute additional statistics on the sentiment data such as geographic analysis and time-series analysis of the data. +