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Journal of Interactive Advertising Volume 20, 2020 - Issue 1
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Articles

Computationally Analyzing Social Media Text for Topics: A Primer for Advertising Researchers

Joseph T. YunDepartment of Accountancy, Gies College of Business, University of Illinois at Urbana–Champaign, Champaign, Illinois, USA; ;Charles H. Sandage Department of Advertising, College of Media, University of Illinois at Urbana–Champaign, Champaign, Illinois, USA; Correspondence[email protected]
ORCID Iconhttp://orcid.org/0000-0001-6875-4456
ORCID Icon,
Brittany R. L. DuffCharles H. Sandage Department of Advertising, College of Media, University of Illinois at Urbana–Champaign, Champaign, Illinois, USA; ORCID Iconhttp://orcid.org/0000-0002-3206-0353
ORCID Icon,
Patrick T. VargasCharles H. Sandage Department of Advertising, College of Media, University of Illinois at Urbana–Champaign, Champaign, Illinois, USA;
,
Hari SundaramDepartment of Computer Science, Grainger College of Engineering, University of Illinois at Urbana–Champaign, Champaign, Illinois, USA;
&
Itai HimelboimDepartment of Advertising and Public Relations, Grady College of Journalism and Mass Communication, University of Georgia, Athens, Georgia, USA
Pages 47-59 | Published online: 31 Dec 2019

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Itai Himelboim, Ewa Maslowska & Theo Araujo. (2023) Integrating Network Clustering Analysis and Computational Methods to Understand Communication With and About Brands: Opportunities and Challenges. Journal of Advertising 0:0, pages 1-11.
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Marla Royne Stafford, Itai Himelboim, Dror Walter & Yotam Ophir. (2023) The evolution of advertising research through four decades: a computational analysis of themes, topics and methods. International Journal of Advertising 42:1, pages 18-41.
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Joanna Strycharz & Claire M. Segijn. (2022) The Future of Dataveillance in Advertising Theory and Practice. Journal of Advertising 51:5, pages 574-591.
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Yang Feng & Huan Chen. (2022) Leveraging Artificial Intelligence to Analyze Consumer Sentiments within Their Context: A Case Study of Always #LikeAGirl Campaign. Journal of Interactive Advertising 22:3, pages 336-348.
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Linwan Wu, Naa Amponsah Dodoo, Taylor Jing Wen & Li Ke. (2022) Understanding Twitter conversations about artificial intelligence in advertising based on natural language processing. International Journal of Advertising 41:4, pages 685-702.
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Jeongwon Yang, Ploypin Chuenterawong & Krittaphat Pugdeethosapol. (2021) Speaking Up on Black Lives Matter: A Comparative Study of Consumer Reactions toward Brand and Influencer-Generated Corporate Social Responsibility Messages. Journal of Advertising 50:5, pages 565-583.
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Apollo Demirel. (2020) An Examination of a Campaign Hashtag (#OptOutside) with Google Trends and Twitter. Journal of Interactive Advertising 20:3, pages 165-180.
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Articles from other publishers (8)

Victoria Broadbridge, Federico Mangió & Giandomenico Di Domenico. (2023) How Brand Managers Can Maximize Engagement with ASMR YouTube Content. Journal of Advertising Research, pages 2023-026.
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Leona Yi-Fan Su, Tianli Chen, Yee Man Margaret Ng, Ziyang Gong & Yi-Cheng Wang. (2023) Integrating Human Insights Into Text Analysis: Semi-Supervised Topic Modeling of Emerging Food-Technology Businesses’ Brand Communication on Social Media. Social Science Computer Review.
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Chiara L. Bernardi & Nouf Alhamdan. (2022) Social media analytics for nonprofit marketing: #Downsyndrome on Twitter and Instagram. Journal of Philanthropy and Marketing 27:4.
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David E. Williams & Spencer P. Greenhalgh. (2022) Pseudonymous academics: Authentic tales from the Twitter trenches. The Internet and Higher Education 55, pages 100870.
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Cécile Zachlod, Olga Samuel, Andrea Ochsner & Sarah Werthmüller. (2022) Analytics of social media data – State of characteristics and application. Journal of Business Research 144, pages 1064-1076.
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Iosif Viktoratos & Athanasios Tsadiras. (2021) Personalized Advertising Computational Techniques: A Systematic Literature Review, Findings, and a Design Framework. Information 12:11, pages 480.
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Sudipta Mandal, Arvind Sahay, Adrian Terron & Kavita Mahto. (2021) How implicit self-theories and dual-brand personalities enhance word-of-mouth. European Journal of Marketing 55:5, pages 1489-1515.
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Curtis Donelson, Carolyn Sutter, Giang V. Pham, Kanika Narang, Chen Wang & Joseph T. Yun. (2021) Using a Machine Learning Methodology to Analyze Reddit Posts regarding Child Feeding Information. Journal of Child and Family Studies 30:5, pages 1290-1298.
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