Social Media Blog Analysis using Watson Analytics

Abstract

Abstract

Analytics is defined as the discovery, interpretation, and communication of meaningful patterns in data. A blog is a discussion or informational website published on the world wide web consisting of discrete, often informal diary-style text entries and may contain unstructured or semi-structured data. The analysis of unstructured data types is current challenge, getting attention in industry. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization and information privacy. Watson analytics is a cloud based smart data discovery tool from IBM analytics. Watson solutions aim to enhance, scale, and accelerate human expertise, targeting a wide range of complex challenges. AlchemyAPI is a collection of APIs that offer text analysis through natural language processing. The keyword extraction API works on URL’s, HTML documents and plain text. It automatically detects the language of the content and then performs the appropriate analysis. AlchemyAPI’s keyword extraction algorithm employs sophisticated statistical algorithms and natural language processing technology aided with machine learning techniques to analyze the content and identify the relevant keywords. The proposed blog analyzer application uses the Alchemy_API’s keyword extraction service, accepts the URL’s of the blogs and processes the content by employing sophisticated statistical algorithms and natural language processing aided with machine learning techniques, to retrieve the related/relevant and rank the keywords of the input content.

Keywords: Blog, keywords, Watson analytics, Alchemy API, keyword extraction service

Cite this Article

Jigali Sindhu B, Nirmala CR. Social Media Blog Analysis using Watson Analytics. Journal of Artificial Intelligence Research & Advances. 2016; 3(3): 15–21p.