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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.
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]
Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Engaging head and heart: effect of marketer-generated content on social media engagement.
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  Data: <searchLink fieldCode="AR" term="%22Chandrasekaran%2C+Shabana%22">Chandrasekaran, Shabana</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Annamalai%2C+Balamurugan%22">Annamalai, Balamurugan</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yoshida%2C+Masayuki%22">Yoshida, Masayuki</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22R%2EV%2E%2C+ShabbirHusain%22">R.V., ShabbirHusain</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pathak%2C+Atul+Arun%22">Pathak, Atul Arun</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Behaviour+%26+Information+Technology%22">Behaviour & Information Technology</searchLink>. Nov2025, Vol. 44 Issue 19, p4713-4733. 21p.
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  Data: <searchLink fieldCode="DE" term="%22Social+media%22">Social media</searchLink><br /><searchLink fieldCode="DE" term="%22Language+%26+languages%22">Language & languages</searchLink><br /><searchLink fieldCode="DE" term="%22Poisson+distribution%22">Poisson distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Teams+in+the+workplace%22">Teams in the workplace</searchLink><br /><searchLink fieldCode="DE" term="%22Sports%22">Sports</searchLink><br /><searchLink fieldCode="DE" term="%22Prompts+%28Psychology%29%22">Prompts (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Consumer+attitudes%22">Consumer attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Scientific+observation%22">Scientific observation</searchLink><br /><searchLink fieldCode="DE" term="%22Content+analysis%22">Content analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Marketing%22">Marketing</searchLink><br /><searchLink fieldCode="DE" term="%22Facebook+%28Web+resource%29%22">Facebook (Web resource)</searchLink><br /><searchLink fieldCode="DE" term="%22Emotions%22">Emotions</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Advertising%22">Advertising</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Communication%22">Communication</searchLink><br /><searchLink fieldCode="DE" term="%22Social+networks%22">Social networks</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Information+science%22">Information science</searchLink><br /><searchLink fieldCode="DE" term="%22Sentiment+analysis%22">Sentiment analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Theory%22">Theory</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Athletic+ability%22">Athletic ability</searchLink><br /><searchLink fieldCode="DE" term="%22Access+to+information%22">Access to information</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Nonparametric+statistics%22">Nonparametric statistics</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22India%22">India</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: 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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  Data: <i>Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/0144929X.2025.2486586
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 21
        StartPage: 4713
    Subjects:
      – SubjectFull: Social media
        Type: general
      – SubjectFull: Language & languages
        Type: general
      – SubjectFull: Poisson distribution
        Type: general
      – SubjectFull: Teams in the workplace
        Type: general
      – SubjectFull: Sports
        Type: general
      – SubjectFull: Prompts (Psychology)
        Type: general
      – SubjectFull: Data analysis
        Type: general
      – SubjectFull: Consumer attitudes
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      – SubjectFull: Scientific observation
        Type: general
      – SubjectFull: Content analysis
        Type: general
      – SubjectFull: Marketing
        Type: general
      – SubjectFull: Facebook (Web resource)
        Type: general
      – SubjectFull: Emotions
        Type: general
      – SubjectFull: Descriptive statistics
        Type: general
      – SubjectFull: Advertising
        Type: general
      – SubjectFull: Statistics
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      – SubjectFull: Communication
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      – SubjectFull: Social networks
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      – SubjectFull: Mathematical models
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      – SubjectFull: Information science
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      – SubjectFull: Sentiment analysis
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      – SubjectFull: Theory
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      – SubjectFull: Data analysis software
        Type: general
      – SubjectFull: Athletic ability
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      – SubjectFull: Regression analysis
        Type: general
      – SubjectFull: Nonparametric statistics
        Type: general
      – SubjectFull: India
        Type: general
    Titles:
      – TitleFull: Engaging head and heart: effect of marketer-generated content on social media engagement.
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              Text: Nov2025
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