A Systematic Analysis of Higher Educational Content Over Social Media for Engagement Optimization

Q4 Business, Management and Accounting

Review of Marketing Science Pub Date : 2023-01-03 DOI:10.1515/roms-2022-0050

Prakrit Saikia, H. Barman

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引用次数: 0

Abstract

Abstract The purpose of this article is to analyze higher educational institutions’ contents in terms of post variables and engagement volume based on categorical classification of theme to understand which factors affect the overall engagement. The sample included 29,814 Facebook, Instagram, and Twitter posts from the top 10 largest and global higher education institutions by community size as of January 1, 2021. The platform’s publically available dashboard metrics were used to analyze the engagement. A negative binomial regression model was used to estimate the impact of selected variables on engagement. Instagram has the highest potential for engagement growth and also dominates the other platforms for engagement per post. Twitter has been observed as the most preferred platform by volume of activity and also the least efficient of all. Facebook has the highest volume of engagement and second-highest efficiency. There is a huge gap between the publisher’s activity priority and engagement pattern across the selected platforms. The findings highlight the importance of developing a systematic procedure for analyzing content engagement potential and designing post strategies for each platform. This study contributes to the literature by designing a framework to analyze post efficiency as per content category for any given platform based on public level data. This adds up to the ability of the competitors with social media to analyze their position in terms of engagement and helps in estimation. These enhancements resulted in a framework with more explanatory power while projecting post efficiency.

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基于社交媒体的高等教育内容参与度优化的系统分析

摘要本文的目的是在主题分类的基础上，从后变量和参与量两个方面分析高等教育机构的内容，以了解哪些因素会影响整体参与。截至2021年1月1日，样本包括来自全球十大高等教育机构的29814条Facebook、Instagram和Twitter帖子（按社区规模划分）。该平台公开可用的仪表板指标用于分析参与度。采用负二项回归模型来估计选定变量对参与度的影响。Instagram的参与度增长潜力最大，在其他平台上也占据主导地位。推特被认为是最受欢迎的活动平台，也是效率最低的平台。Facebook的参与度最高，效率第二。在选定的平台上，出版商的活动优先级和参与模式之间存在巨大差距。研究结果强调了开发一个系统的程序来分析内容参与潜力和为每个平台设计帖子策略的重要性。本研究通过设计一个框架来分析基于公共层面数据的任何给定平台的内容类别的帖子效率，为文献做出了贡献。这增加了社交媒体竞争对手在参与度方面分析其地位的能力，并有助于评估。这些改进产生了一个在预测员额效率的同时具有更大解释力的框架。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Review of Marketing Science Business, Management and Accounting-Marketing

CiteScore

1.10

自引率

0.00%

发文量

期刊介绍： The Review of Marketing Science (ROMS) is a peer-reviewed electronic-only journal whose mission is twofold: wide and rapid dissemination of the latest research in marketing, and one-stop review of important marketing research across the field, past and present. Unlike most marketing journals, ROMS is able to publish peer-reviewed articles immediately thanks to its electronic format. Electronic publication is designed to ensure speedy publication. It works in a very novel and simple way. An issue of ROMS opens and then closes after a year. All papers accepted during the year are part of the issue, and appear as soon as they are accepted. Combined with the rapid peer review process, this makes for quick dissemination.