Decoding User Interaction Dynamics on Facebook Fan Page: A Sentiment Mining Approach

Abstract

Increased presence of firms on social media like Facebook has enabled users to interact directly with the firms. As this platform is used for brand promotions, it is important for firms to understand the dynamics of user interaction that happens on the brand’s fan page. This study investigates the influence of marketer-generated content (MGC) and the recursive effect of sentiments on user interaction with the help of sentiment mining approach and negative binomial regression. The analysis is done over 2,121 marketers’ content and 22 million user content across the top five Facebook brand pages in India. The results show that an increase in positive comment sentiment triggers increased liking and sharing behaviour by the users on the marketers’ content. Moreover, users are more inclined to like and share on marketers’ contents that are informative posts. Posts containing images garner higher likes and comments, but videos have higher shares. The results are useful for the brands to understand user behaviour on a brand’s social media fan page.

Keywords

Facebook fan page sentiment mining social media user interaction

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