The tremendous growth of the social networks has paved way for social interactions of investing communities about a company's stock performance. Web 2.0 platforms give people more power over the way they share information and exchange stock opinions. Investors are able to share their comments on stocks using the social media platforms. These interactions are captured and mined to produce advice on investing which helps retail investors to do prospective investments to increase profits. This book proposes a novel stock ...
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The tremendous growth of the social networks has paved way for social interactions of investing communities about a company's stock performance. Web 2.0 platforms give people more power over the way they share information and exchange stock opinions. Investors are able to share their comments on stocks using the social media platforms. These interactions are captured and mined to produce advice on investing which helps retail investors to do prospective investments to increase profits. This book proposes a novel stock recommendation methodology using Bio-inspired Computing Techniques. This method extracts sentiments from the investor's stock reviews crawled from Twitter and performs the sentiment analysis, which is optimized by the Bio-Inspired Computing Techniques.
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Add this copy of Bio-Inspired Computing Techniques for Social Stock to cart. $87.51, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2025 by LAP Lambert Academic Publishing.
