Social media analytics for YouTube comments: potential and limitations |
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Authors: | Mike Thelwall |
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Affiliation: | School of Mathematics and Computing, University of Wolverhampton, Wolverhampton, UK |
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Abstract: | The need to elicit public opinion about predefined topics is widespread in the social sciences, government and business. Traditional survey-based methods are being partly replaced by social media data mining but their potential and limitations are poorly understood. This article investigates this issue by introducing and critically evaluating a systematic social media analytics strategy to gain insights about a topic from YouTube. The results of an investigation into sets of dance style videos show that it is possible to identify plausible patterns of subtopic difference, gender and sentiment. The analysis also points to the generic limitations of social media analytics that derive from their fundamentally exploratory multi-method nature. |
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Keywords: | Social media analytics YouTube comments opinion mining gender sentiment issues |
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