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Social Media Content Analysis: Machine Learning
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Author(s): D. Sudaroli Vijayakumar (PES University, Bangalore, India), Senbagavalli M. (Alliance University, Bangalore, India), Jesudas Thangaraju (Mahendra Engineering College (Autonomous), Namakkal, India)and Sathiyamoorthi V. (Sona College of Technology, Salem, India)
Copyright: 2021
Pages: 19
Source title:
Challenges and Applications of Data Analytics in Social Perspectives
Source Author(s)/Editor(s): V. Sathiyamoorthi (Sona College of Technology, India)and Atilla Elci (Hasan Kalyoncu University, Turkey)
DOI: 10.4018/978-1-7998-2566-1.ch009
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Abstract
Today's wealth and value are data. Data, used sensibly, are making wonders to make wise decisions for individuals, corporates, etc. The era of spending time with an individual to understand them better is gone. Individual's interests, requirements are identified easily by observing the activities an individual performs in social media. Social media, started as a tool for interaction, has grown as a platform to make and promote business. Social media content is unavoidable as the data that are going to be dealt with is huge in volume, variety, and velocity. The demand for using machine learning in analysing social media content is increasing at a faster pace in identifying influencers, demands of individuals. However, the real complexity lies in making the data from social media suitable for analysis. The type of data from social media content may be audio, video, image. The chapter attempts to give a comprehensive overview of the various pre-processing methods involved in dealing the social media content and the usage of right algorithms at the right time with suitable case examples.
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