 Twitter data analytical methodology development for prediction of start-up firms’ social media marketing levelSang Hoon Jung and Yong Jin Jeong Technology in Society, 2020, vol. 63, issue C Abstract: Social media marketing is an essential and important tool for start-up firms, which can help start-up firms remedy the marketing limitations through ease and relatively low costs. Predicting start-up firms’ social media engagement level can allow them to gauge the effectiveness of their social media marketing efforts and can provide numerous benefits related to strategic marketing processes. This study focuses on developing a methodology involving data science processes and machine learning models to account for the ongoing advancement of business intelligence methodologies. This study gathered data of 8,434 start-up firms from Twitter, generated social media-based features, and created machine learning models to predict the social media engagement level of each firm. The results show that deep learning provides the best accuracy in predicting the engagement levels. The results also show that the number of tweets by the firms, the number of retweets received, and the number of likes received have the most significance in determining the effectiveness of social media marketing activities. Keywords: Social media; Marketing; Data analysis; Machine learning; Start-ups (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:63:y:2020:i:c:s0160791x19306621 DOI: 10.1016/j.techsoc.2020.101409 Access Statistics for this article Technology in Society is currently edited by Charla Griffy-Brown More articles in Technology in Society from Elsevier |
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