Is sentiment analysis useful in a field as impacted as finance? A grey area of prediction within investments has always been the “buzz” in current events, generated by news sources and general responses. From an outsider’s viewpoint, these events do have an effect on pricing, but how do we determine if it is a negative or if it is a positive effect? NN IP has found predictive value in sentiment analysis.
A quote within a recent MarketsMedia article states, “… found that sentiment data makes a meaningful contribution of between 10% to 15% in our investment scorecards.” This is incredible due to the feed of purely “buzz” has this much determined weight on influential decisions about the investment market. Sentiment analysis itself is slowly building up to becoming one of the world’s most industry-versatile machine learning algorithms, purely because the very use of text as data has not been recorded nor thought of as data before & with this type of analysis, everywhere that text builds upon: Twitter feeds, street address, even just pure reviews online & the words people respond to one another will be useful.
Whether you have a financial background or not, sentiment analysis will more than open your eyes on a flourish of other topics, such as determining the status of your product. But like all aspects that give us knowledge, to effectively use these algorithms, a background is required. Luckily, we have a portion of our quick and detailed boot camp that covers the beginnings of sentiment analysis to help you adjust to these new techniques.
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