Detecting sentiment through text mining analysis.

Data mining has significantly grown in popularity over the last decade because of its ability to detect hidden patterns in big data. With the rise of Web 2.0 and social media, text mining should become a focus for businesses as well. With sites like Yelp, Facebook, and Twitter, customers now have the ability to publicly shout their resentments or endearments of a company and be heard. It can be expensive for businesses to pay attention to every comment made on the vast social web. Text mining social sites can help by automating this process. A text mining sentiment algorithm could be used to provide a general daily sentiment of one's business. A sentiment algorithm analyzes language to determine whether a post's sentiment is positive or negative, shown by percentages. If a general negative sentiment is detected, one might be able to drill down to individual posts to address problems. Using a general sentiment key performance indicator can help businesses quickly assess their current online reputation. Try out the sentiment widget that I created, found at the top of my homepage: http://www.peterschlamp.com/