Two Decades of Emoticons and Emojis in Consumer Behavior Research: Bibliometric Networks, Geographical Atlas and Classical Roots
DOI:
https://doi.org/10.52152/RCR.V13.4Keywords:
Emoticons, Emojis, Consumer Behavior, Bibliometrics, RPYSAbstract
Emoticons and emojis research have recently witnessed exponential growth. In this article, 261 Scopus peer-reviewed articles related to emoticons and emojis in consumer research are examined using bibliometric techniques. The articles were written by 762 authors from 47 countries over two decades (2000–2023). By so doing, emoticons and emojis research influential authors and journals, emerging trends, collaboration networks, and historical roots are scrutinized. Our findings show that the most relevant outlets publishing Emoticons and emojis research are Food Quality and Preference, Food Research International, Journal of Sensory Studies, Frontiers in Psychology, and Computers in Human Behavior. Thematic evolution analysis revealed a move away from the well-established emoticons and emojis research themes like “microblog” and “emoticon” to new topics such as “consumer/customer engagement” and “natural language processing”. Results also show that there is limited cross-cultural collaboration in emoticons and emojis research. Finally, the “citation classics” of emoticons and emojis research are detected using the reference publication year spectroscopy (RPYS).
References
Arya, V., Sethi, D., & Verma, H. (2018). Are emojis fascinating brand value more than textual language? Mediating role of brand communications to SNS and brand attachment: An insight from India. Corporate Communications, 23, 648-670.
Ávila-Robinson, A., & Wakabayashi, N. (2018). Changes in the structures and directions of destination management and marketing research: A bibliometric mapping study, 2005–2016, Journal of Destination Marketing & Management, 10, 101-111.
Baek, T., Kim, S., Yoon, S., Choi, Y., Choi, D., & Bang, H. (2022). Emojis and assertive environmental messages in social media campaigns. Internet Research, 32, 988-1002.
Bai, Q., Dan, Q., Mu, Z., & Yang, M. (2019). A systematic review of emoji: Current research and future perspectives. Frontiers in Psychology, 10, 2221.
Banckendorff, P. (2009). Themes and trends in Australian and New Zealand tourism research: A social network analysis of citations in two leading journals (1994–2007). Journal of Hospitality and Tourism Management, 16, 1-15.
Beattie, A., Edwards, A., & Edwards, C. (2020). A bot and a smile: Interpersonal impressions of chatbots and humans using emoji in computer-mediated communication. Communication Studies, 71, 409-427.
Buchholz, K. (2024). In 2025, Global Emoji Count Could Grow to 3,790. Retrieved from https://www.statista.com/chart/17275/number-of-emojis-from-1995-bis-2019/
Callon, M., Courtial, J., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry. Scientometrics, 22, 155-205.
Casado-Molina, A., Rojas de Garcia, M., Alarcon-Urbistondo, P., & Romero-Charneco, M. (2022). Exploring the opportunities of the emojis in brand communication: The case of the bear industry. International Journal of Business Communications, 59, 315-333.
Chen, C., & Leydesdorff, L. (2014). Patterns of connections and movements in dual-map overlays: A new method of publication portfolio analysis. Journal of the Association for Information Science and Technology, 65, 334-351.
Chen, C., Song, I., Yuan, X., & Zhang, J. (2008). The thematic and citation landscape of data and knowledge engineering (1985–2007). Data & Knowledge Engineering, 67, 234-250.
Chen, X., & Liu, Y. (2020). Visualization analysis of high-speed railway research based on CiteSpace. Transport Policy, 85, 1-17.
Chew, C., & Eysenbach, G. (2010). Pandemics in the age of Twitter: Content analysis of Tweets during the 2009 H1N1 outbreak. PLoS ONE, 5(11), e14118.
Cini, C. (2022). How emojis became a political language of symbols. Retrieved from https://www.lemonde.fr/en/pixels/article/2022/12/03/howe-emojis-became-a-political-language-of-symbols_6006472_13.html
Cobo, M., Lopez-Herrera, A., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the fuzzy sets theory field. Journal of Informetrics, 5, 146-166.
Corbet, S., Dowling, M., Gao, X., Huang, S., Lucey, B., & Vigne, S. (2019). An analysis of the intellectual structure of research on financial economics of precious metals. Resources Policy, 63, 101416.
Coyle, M., & Carmichael, C. (2019). Perceived responsiveness in text messaging: The role of emoji use. Computers in Human Behavior, 99, 181-189.
Cramer, H., De Juan, P., & Tetreault, J. (2016, September). Sender-intended functions of emojis in US messaging. In Proceedings of the 18th international conference on human-computer interaction with mobile devices and services (pp. 504-509). https://doi.org/10.1145/2935334.2935370
Daniel, T., & Camp, A. (2020). Emojis affect processing fluency on social media. Psychology of Popular Media Culture, 9, 208-213.
Das, G., Wiener, H., & Kareklas, I. (2019). To emoji or not to emoji? Examining the influence of emoji on consumer reactions to advertising. Journal of Business Research, 96, 147-156.
Derks, D., Bos, A., & von Grumbkow, J. (2008). Emoticons and online message interpretation. Social Science Computer Review, 26, 379-388.
Ding, Y. (2011). Scientific collaboration and endorsement: Network analysis of co-authorship and citation networks. Journal of Informetrics, 5, 187-203.
Elango, B., & Rajendran, P. (2012). Authorship trends and collaboration pattern in the marine sciences literature: A scientometric study. International Journal of Information Dissemination and Technology, 2, 166-169.
Evans, V. (2015). No, the rise of the emoji doesn’t spell the end of language. Retrieved from https://www.bangor.ac.uk/news/archive/no-the-rise-of-the-emoji-doesn-t-spell-the-end-of-language-22914
Fang, S., Wei, Y., & Wang, S. (2023). 30 years of exchange rate analysis and forecasting: A bibliometric review. Journal of Economic Surveys, 1-35.
Firdaus, A., Ab Razak, M., Feizollah, A., Hashem, I., Hazim, M., & Anuar, N. (2019). The rise of “blockchain”: Bibliometric analysis of blockchain study. Scientometrics, 120, 1289-1331.
Fomina, Y., Glinska-Newes, A., & Ignasiak-Szulc, A. (2022). Community supported agriculture: Setting the research agenda through a bibliometric analysis. Journal of Rural Studies, 92, 294-305.
Gallo, K., Swaney-Steuve, M., & Chambers, D. (2017). A focus group approach to understanding food-related emotions with children using words and emojis. Journal of Sensory Studies, 32, e12264.
Ganster, T., Eimler, S., & Kramer, N. (2012). Same same but different? The differential influence of smiles and emoticons on person perception. Cyberpsychology, Behavior, and Social Networking, 15, 226-230.
Gibson, W., Huang, P., & Yu, Q. (2018). Emoji and communicative action: The semiotics, sequence and gestural actions of “face covering hand”. Discource, Context & Media, 26, 91-99.
Glänzel, W., & Schubert, A. (2004). Analysing scientific networks through co-authorship. In H. Moed, W. Glanzel, & U. Schmoch (Eds.), Handbook of quantitative science and technology research: The use of publication and patent statistics in studies of S&T systems (pp. 257-276). Dordrecht, Netherlands: Springer.
Gonzales-Valiente, C. (2019). Redes de citación de revistas iberoamericanas de bibliotecología y ciencia de la información en Scopus. Bibliotecas Anales de Investigación, 15, 83-98.
Hennig-Thurau, T., Gwinner, K., Walsh, G., & Gremler, D. (2004). Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet?. Journal of Interactive Marketing, 18, 38-52.
Himelboim, I., Smith, M., & Shneiderman, B. (2013). Tweeting apart: Applying network analysis to detect selective exposure clusters in Twitter. Communication Methods and Measures, 7, 195-223.
Hsu, L., & Chen, Y. (2020). Neuromarketing, subliminal advertising, and hotel selection: An EEG study. Australasian Marketing Journal, 28, 200-208.
Jaeger, S. R., Lee, S. M., Kim, K. O., Chheang, S. L., Jin, D., & Ares, G. (2017). Measurement of product emotions using emoji surveys: Case studies with tasted foods and beverages. Food Quality and Preference, 62, 46–59.
Jiang, Y., Ritchie, B., & Benckendorff, P. (2019). Bibliometric visualization: An application to tourism crisis and disaster research: Current Issues in Tourism, 22, 1925-1957.
Kaye, L., Wall., L., & Malone, S. (2016). Turn that frown upside-down: A contextual account of emoticon usage on different virtual platforms. Computers in Human Behavior, 60, 463-467.
Keller, K. (2003). Brand synthesis: The multidimensionality of brand knowledge. Journal of Consumer Research, 29, 595-600.
Kessler, K. (1963). Bibliographic coupling between scientific papers. Journal of the Association for Information Science and Technology, 14, 10-25.
Khan, G., & Wood, J. (2016). Knowledge networks of the information technology management domain: A social network analysis approach. Communications of the Association for Information Systems, 39, 367-397.
Knoke, D., & Yang, S. (2010). Social Network Analysis. Los Angeles, CA: Sage.
Kralj Novak, P., Smailović, J., Sluban, B., & Mozetič, I. (2015). Sentiment of emojis. PLoS ONE, 10(12), e0144296.
Law, J., Bauin, S., Courtial, J., & Wittaker, J. (1988). Policy and the mapping of scientific change: A co-word analysis of research into environmental acidification. Scientometrics, 14, 251-264.
Lefebvre, S., Boman, L., & Orlowski, M. (2024). Look on the bright side: Emojis impact tipping behavior. International Journal of Hospitality Management, 117, 103653.
Li, X., Chan, K., & Kim, S. (2019). Service with emoticons: How customers interpret employee use of emoticons in online service encounters. Journal of Consumer Research, 45, 973-987.
Li, Y., & Shin, H. (2023). Should a luxury brand’s chatbot use emoticons? Impact on brand status. Journal of Consumer Behavior, 22, 569-581.
Liao, H., Tang, M., Li, Z., & Lev, B. (2019). Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on essential science indicators. Omega, 88, 228-236.
Liu, D., Lv, Y., & Huang, W. (2023). How do consumers react to chatbots’ humorous emojis in service failures. Technology in Society, 73, 102244.
Lohmann, K., Pyka, S., & Zanger, C. (2017). The effects of smileys or receivers’ emotions. Journal of Consumer Marketing, 34, 489-495.
Lu, X., Ai, W., Liu, X., Li, Q., Wang, N., Huang, G., & Mei, Q. (2016). Learning from the ubiquitous language: An empirical analysis of emoji usage of smartphone users. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 770-780). New York, NY: ACM Press.
Ma, R., & Wang, W. (2021). Smile or pity? Examine the impact of emoticon valence on customer satisfaction and purchase intention. Journal of Business Research, 134, 443-456.
Marx, W., Haunschild, R., Thor, A., & Bornmann, L. (2017). Which works are cited most frequently in climate change research literature? A bibliometric approach based on reference publication year spectroscopy. Scientometrics, 110, 335-353.
McPherson, M., Smith-Lovin, L., & Cook, J. (2001). Birds of feather: Homophily in social networks. Annual Review of Sociology, 27, 415-444.
McShane, L., Pancer, E., Poole, M., & Deng, Q. (2021). Emoji, playfulness, and brand engagement on Twitter. Journal of Interactive Marketing, 53, 96-110.
Milgram, S. (1967). The small-world problem. Psychology Today, 2, 60-67.
Moussa, S. (2019). An emoji-based metric for monitoring consumers’ emotions toward brands on social media. Marketing Intelligence and Planning, 37, 211-225.
Neff, M., & Corley, E. (2009). 35 years and 160,000 articles: A bibliometric exploration of the evolution of ecology. Scientometrics, 80, 657-682.
Neuhaus, C., Neuhaus, E., Asher, A., & Wrede, C. (2006). The depth and breadth of Google Scholar: An empirical study. Libraries and the Academy, 6, 127-141.
Newman, M., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69, 1-15.
Park, S., Lim, Y., & Park, H. (2015). Comparing Twitter and YouTube networks in information diffusion: The case of the “Occupy Wall Street” movement. Technological Forecasting & Social Change, 95, 208-217.
Prada, M., Rodrigues, D., Garrido, M., Lopes, D., Cavalheiro, B., & Gaspar, R. (2018). Motives, frequency and attitudes toward emoji and emoticon use. Telematics and Informatics, 35, 1925-1934.
Qian, J., Law, R., & Wei, J. (2019). Knowledge mapping in travel website studies: A scientometric review. Scandinavian Journal of Hospitality and Tourism, 19, 192-209.
Rodrigues, D., Prada, M., Gspar, R., Garrido, M., & Lopes, D. (2018). Lisbon emoji end emoticon database (LEED): Norms for emoji and emoticons in seven evaluative dimensions. Behavior Research Methods, 50, 392-405.
Sadeghi-Niaraki, A. (2023). Internet of Things (IoT) review of review: Bibliometric overview since its foundation. Future Generation Computer Systems, 143, 361-377.
Schouteten, J. J., Verwaeren, J., Almli, V., & Rini, L. (2022). Comparing a product-specific versus a general emoji list to measure consumers’ emotional associations with chocolate and predict food choice. Food Research International, 157, 86-97.
Schouteten, J., Verwaeren, J., Gellynck, X., & Almli, V. (2019). Comparing a standard to a product-specific emoji list for evaluating food products by children. Food Quality and Preference, 72, 86-97.
Schultz, F., Utz, S., & Goritz, A. (2011). Is the medium the message? Perceptions of and reactions to crisis communication via Twitter, blogs and traditional media. Public Relations Review, 37, 20-27.
Schultz, P., Nolan, J., Cialdini, R., Goldstein, N., & Griskevicius, V. (2007). The constructive, destructive, and reconstructive power of social norms. Psychological Science, 18, 429-434.
Shirky, C. (2008). The power of organizing without organizations. New York, NY: Penguin Press.
Skovholt, K., Gronning, A., & Kankaanranta, A. (2014). The communicative function of emoticons in workplace e-mails. Journal of Computer-Mediated Communication, 19, 780-797.
Smith, L., & Rose, R. (2020). Service with a smiley face: Emojional contagion in digitally mediated relationships. International Journal of Research in Marketing, 37, 301-319.
Smith, N., & Graham, T. (2019). Mapping the anti-vaccination movement on Facebook. Information, Communication & Society, 22, 1310-1327.
The R Core Team. (2023). R: A language and environment for statistical computing (Version 3.3.1). Retrieved from https://web.mit.edu/r_v3.3.1/fullrefman.pdf
Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., & Kappas, A. (2010). Sentiment strength detection in short informal text. Journal of the American Society for Information Science and Technology, 61, 2544-2558.
Thor, A., Bornmann, L., Marx, W., & Mutz, R. (2018). Identifying single influential publications in a research field: New analysis opportunities of the CRExplorer. Scientometrics, 116, 591-608.
Thor, A., Marx, W., Leydesdorff, L., & Bornmann, L. (2016). Introducing CitedReferenceExplorer (CRExplorer): A program for reference publication year spectroscopy with cited references standardization. Journal of Informetrics, 10, 508-515.
van Eck, N., & Waltman, L. (2014). CitNetExplorer: A new software tool for analyzing and visualizing citation networks. Journal of Informetrics, 8, 802-823.
van Eck, N., & Waltman, L. (2019). VOSviewer Manual: Manual for VOSviewer version 1 .6.13. Retrieved from https://www.vosviewer.com/documentation/Manual_VOSviewer_1.6.13.pdf
Vanni, T., Mesa-Frias, M., Sanchez-Garcia, R., Roesler, R., Schwartsmann, G., Goldani, M. Z., & Foss, A. M. (2014). International scientific collaboration in HIV and HPV: Anetwork analysis. PLoS ONE, 9(3), e93376.
Vidal., L., Ares, G., & Jaeger, S. (2016). Use of emoticons and emoji in tweets for food-related emotional expression. Food Quality and Preference, 49, 119-128.
Volker, J., & Mannheim, C. (2021). Turned in on senders’ self-revelation: Emojis and emotional intelligence influence interpretation of WhatsApp messages. Computers in Human Behavior Reports, 3, 100062.
Walther, J. B., & D’Addario, K. P. (2001). The impacts of emoticons on message interpretation in computer-mediated communication. Social Science Computer Review, 19, 324-347.
Wei, Y., Wang, J., Chen, T., Yu, B., & Liao, H. (2018). Frontiers of low-carbon technologies: Results from bibliographic coupling with sliding window. Journal of Cleaner Production, 190, 422-431.
Wider, W., Gao, Y., Chan, C., Lin, J., Li, J., Tanucan, J., & Fauzi, M. (2023). Unveiling trends in digital tourism research: A bibliometric analysis of co-citation and co-word analysis. Environmental and Sustainability Indicators, 20, 100308.
Wolf, A. (2000). Emotional expression online: Gender differences in emoticon use. CyberPsychology & Behavior, 3, 827-833.
Zhu, J., & Hua, W. (2017). Visualizing the knowledge domain of sustainable development research between 1987 and 2015: A bibliometric analysis. Scientometrics, 110, 893-914.
Zou, X., Yue, W., & Vu, H. (2018). Visualization and analysis of mapping knowledge domain of road safety. Accident Analysis and Prevention, 118, 131-145.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The philosophy of the journal is to be open and to make all articles accessible. It is our belief that open access is a must in the future of science.
Authors who publish with RCR accept a slightly modified Creative Commons Attribution-NonCommercial 3.0 Unported License.
You, as author, retain the copyrights for your paper, but the Review of Communication Research is granted exclusivity for publication of the article. The agreement allows others to share the work with an acknowledgement of the work's authorship and publication in this journal. We do not want third parties to make a commercial use of the article, unless we agree it with authors.
The journal will run an open review process as well as a traditional peer review process.
When the manuscript is accepted for publication, it will get a doi number and get available online to facilitate early citation.
The journal will post the published article to many public repositories for further diffusion and permanence.
You, as author, are permitted and encouraged to post your work online (e.g., in institutional repositories or on your website), as it can lead to productive exchanges, as well as earlier and greater citation of published work.
If you have any doubts, please, contact the editor: editor@rcommunication.org
Many thanks for submitting your work to this journal.
