Engaging head and heart: effect of marketer-generated content on social media engagement.
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| Title: | Engaging head and heart: effect of marketer-generated content on social media engagement. |
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| Authors: | Chandrasekaran, Shabana (AUTHOR), Annamalai, Balamurugan (AUTHOR), Yoshida, Masayuki (AUTHOR), R.V., ShabbirHusain (AUTHOR), Pathak, Atul Arun (AUTHOR) |
| Source: | Behaviour & Information Technology. Nov2025, Vol. 44 Issue 19, p4713-4733. 21p. |
| Subjects: | Social media, Language & languages, Poisson distribution, Teams in the workplace, Sports, Prompts (Psychology), Data analysis, Consumer attitudes, Scientific observation, Content analysis, Marketing, Facebook (Web resource), Emotions, Descriptive statistics, Advertising, Statistics, Communication, Social networks, Mathematical models, Information science, Sentiment analysis, Theory, Data analysis software, Athletic ability, Access to information, Regression analysis, Nonparametric statistics |
| Geographic Terms: | India |
| Abstract: | Social media engagement (SME) is crucial for sports clubs to build strong relationships and realise financial gains. To drive SME, sports clubs must focus on 'what to post' and 'how to communicate it' on social media. The research addresses this by studying the impact of informational and non-informational cues embedded in social media posts. This study draws upon the elaboration likelihood model (ELM) of persuasion. We identify five features (content type, language complexity, visual complexity, media richness, and content sentiment) influencing users' SMEs. A qualitative content analysis is conducted to classify the content type, while the Linguistic Inquiry and Word Count (LIWC) dictionary is used to analyse the linguistic characteristics of the social media posts. Finally, Poisson regression analysis investigates the effect of content characteristics on SME measures, namely likes, comments, and shares on Facebook posts. A total of 1,880 Facebook posts (registering over 45 million impressions) by four cricket clubs from the Indian Premier League were analysed. The study empirically validates content features that aid/impede information processing to positively/negatively impact users' SME. This research contributes to social media communication by demonstrating linguistics as an effective approach to enhancing SME outcomes. [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | Social media engagement (SME) is crucial for sports clubs to build strong relationships and realise financial gains. To drive SME, sports clubs must focus on 'what to post' and 'how to communicate it' on social media. The research addresses this by studying the impact of informational and non-informational cues embedded in social media posts. This study draws upon the elaboration likelihood model (ELM) of persuasion. We identify five features (content type, language complexity, visual complexity, media richness, and content sentiment) influencing users' SMEs. A qualitative content analysis is conducted to classify the content type, while the Linguistic Inquiry and Word Count (LIWC) dictionary is used to analyse the linguistic characteristics of the social media posts. Finally, Poisson regression analysis investigates the effect of content characteristics on SME measures, namely likes, comments, and shares on Facebook posts. A total of 1,880 Facebook posts (registering over 45 million impressions) by four cricket clubs from the Indian Premier League were analysed. The study empirically validates content features that aid/impede information processing to positively/negatively impact users' SME. This research contributes to social media communication by demonstrating linguistics as an effective approach to enhancing SME outcomes. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 0144929X |
| DOI: | 10.1080/0144929X.2025.2486586 |
