Sentiment Analysis

Sentiment analysis aims to automatically identify the feeling, emotion, or intent behind a given text using various text-mining techniques. The most obvious advantage of these automated tools is their ability to evaluate large quantities of text, without manual intervention.

The academic field of sentiment analysis, and various associated software tools, are not a new phenomenon, and have been in mainstream commercial use since around 2001. Initially, these tools were used for analysis of sentiment surrounding specific products on popular product review sites. Later, they were applied to evaluating brand value for corporations. Most recently, tools to measure sentiment have been successfully and commercially applied to the stock market advice domain.

What is Sentiment?

Sentiment is defined as a thought, view, or attitude. Arguably, what people feel - and especially what this impels them to do - is the driving force behind human economics, and the glue that binds human society itself.

Thus, the importance of sentiment analysis – which enables large-scale understanding and clarity regarding the feelings of a group of people on a given subject – cannot be underestimated. For political, commercial, and even religious purposes, sentiment analysis tools can offer insight that is valuable both monetarily and socially.

Where is Sentiment?

Quantifiable sentiment analysis, based on a large-scale sentiment dictionary, has of course been facilitated by the ready availability of the immense and classifiable body of data that is the Internet.

In fact, the Internet has not only facilitated the development of sentiment analysis tools, it has actually necessitated it. For any given subject, there exists such a vast amount of information on the Internet as to make manual review and processing infeasible. Thus, in a very real sense, one of the few ways we can make sense of any subject based on web-originated data is via tools that measure sentiment.

How is Sentiment Analysis Used?

As mentioned above, there are number commercial uses for sentiment analysis tools. One field is stock market advice, in which these tools have been especially effective in sorting through and making sense of reams of data.

The stock market is an excellent example of a closed and measurable system that is almost entirely sentiment-driven. Investors know that the stock market isn’t just about P/E, EPS, or Market Cap. It is the unstructured dinner party chat, the gossip, the rumor, the opinion, and the gut feelings that shape the market.

For this reason, software like The Stock Sonar has shown such promise in harnessing the fiscal power of sentiment. By effectively and accurately measuring the prevailing sentiment in forums, blogs, documents, Tweets, and mainstream and niche media, sentiment analysis tools like The Stock Sonar examine unstructured data from multiple sources, and then intelligently weigh and score the findings on a numeric scale. This ultimately offers investors an effective method to mine insights from analysts, media, social media, and company announcements – granting them a clearer understanding of the effect of sentiment on stock values, and delivering a competitive investing edge.