ABSTRACT
Emojis are commonly used as non-verbal cues in texting, yet may also lead to misunderstandings due to their often ambiguous meaning. User personality has been linked to understanding of emojis isolated from context, or via indirect personality assessment through text analysis. This paper presents the first study on the influence of personality (measured with BFI-2) on understanding of emojis, which are presented in concrete mobile messaging contexts: four recipients (parents, friend, colleague, partner) and four situations (information, arrangement, salutory, romantic). In particular, we presented short text chat scenarios in an online survey (N=646) and asked participants to add appropriate emojis. Our results show that personality factors influence the choice of emojis. In another open task participants compared emojis found as semantically similar by related work. Here, participants provided rich and varying emoji interpretations, even in defined contexts. We discuss implications for research and design of mobile texting interfaces.
- Wei Ai, Xuan Lu, Xuanzhe Liu, Ning Wang, Gang Huang, and Qiaozhu Mei. 2017. Untangling Emoji Popularity Through Semantic Embeddings.. In International AAAI Conference on Web and Social Media. AAAI Publications, Palo Alto, CA, USA, 2--11.Google Scholar
- Fathiya Al Rashdi. 2015. Forms and functions of emojis in WhatsApp interaction among Omanis. Ph.D. Dissertation. Georgetown University.Google Scholar
- Sean Andrist, Bilge Mutlu, and Adriana Tapus. 2015. Look Like Me: Matching Robot Personality via Gaze to Increase Motivation. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). ACM, New York, NY, USA, 3603--3612. https://doi.org/10.1145/2702123.2702592Google ScholarDigital Library
- Francesco Barbieri, Miguel Ballesteros, and Horacio Saggion. 2017. Are Emojis Predictable? CoRR abs/1702.07285 (2017), 7. http://arxiv.org/abs/1702.07285Google Scholar
- Francesco Barbieri, German Kruszewski, Francesco Ronzano, and Horacio Saggion. 2016. How Cosmopolitan Are Emojis?: Exploring Emojis Usage and Meaning over Different Languages with Distributional Semantics. In Proceedings of the 24th ACM International Conference on Multimedia (MM '16). ACM, New York, NY, USA, 531--535. https://doi.org/10.1145/2964284.2967278Google ScholarDigital Library
- Francesco Barbieri, Francesco Ronzano, and Horacio Saggion. 2016. What does this emoji mean? A vector space skip-gram model for Twitter emojis. In Proceedings of Language Resources and Evaluation Conference. ELRA (European Language Resources Association), 6.Google Scholar
- Agathe Battestini, Vidya Setlur, and Timothy Sohn. 2010. A Large Scale Study of Text-messaging Use. In Proceedings of the 12th International Conference on Human Computer Interaction with Mobile Devices and Services (MobileHCI '10). ACM, New York, NY, USA, 229--238. https://doi.org/10.1145/1851600.1851638Google ScholarDigital Library
- J. Biel and D. Gatica-Perez. 2013. The YouTube Lens: Crowdsourced Personality Impressions and Audiovisual Analysis of Vlogs. IEEE Transactions on Multimedia 15, 1 (Jan 2013), 41--55. https://doi.org/10.1109/TMM.2012.2225032Google ScholarDigital Library
- Peter Borkenau and Anette Liebler. 1992. Trait inferences: Sources of validity at zero acquaintance. Journal of Personality and Social Psychology 62, 4 (1992), 645. https://doi.org/10.1037/0022-3514.62.4.645Google ScholarCross Ref
- Burge, Jeremy. 2017. 5 Billion Emojis Sent Daily on Messenger. https://blog.emojipedia.org/5-billion-emojis-sent-daily-on-messenger/, last accessed: 2019-01-30.Google Scholar
- Judee K Burgoon, Laura K Guerrero, and Kory Floyd. 2016. Nonverbal communication. Routledge, New York, NY, USA.Google Scholar
- Daniel Buschek, Mariam Hassib, and Florian Alt. 2018. Personal Mobile Messaging in Context: Chat Augmentations for Expressiveness and Awareness. ACM Trans. Comput.-Hum. Interact. 25, 4, Article 23 (Aug. 2018), 33 pages. https://doi.org/10.1145/3201404Google ScholarDigital Library
- Donn Byrne. 1961. Interpersonal attraction and attitude similarity. The Journal of Abnormal and Social Psychology 62, 3 (1961), 713--715. https://doi.org/10.1037/h0044721Google ScholarCross Ref
- Anne Campbell and J. Philippe Rushton. 1978. Bodily communication and personality. British Journal of Social and Clinical Psychology 17, 1 (1978), 31--36. https://doi.org/10.1111/j.2044-8260.1978.tb00893.xGoogle ScholarCross Ref
- Zhenpeng Chen, Xuan Lu, Wei Ai, Huoran Li, Qiaozhu Mei, and Xuanzhe Liu. 2018. Through a Gender Lens: Learning Usage Patterns of Emojis from Large-Scale Android Users. In Proceedings of the 2018 World Wide Web Conference (WWW '18). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 763--772. https://doi.org/10.1145/3178876.3186157Google ScholarDigital Library
- Herbert H. Clark. 1996. Using language. Cambridge University Press, Cambridge, UK.Google Scholar
- Paul T Costa and Robert R McCrae. 1980. Influence of extraversion and neuroticism on subjective well-being: happy and unhappy people. Journal of Personality and Social Psychology 38, 4 (1980), 668. https://doi.org/10.1037/0022-3514.38.4.668Google ScholarCross Ref
- Paul T Costa Jr and Robert R McCrae. 1992. Four ways five factors are basic. Personality and Individual Differences 13, 6 (1992), 653--665. https://doi.org/10.1016/0191-8869(92)90236-IGoogle ScholarCross Ref
- Stéphane Côté and Debbie S Moskowitz. 1998. On the dynamic covariation between interpersonal behavior and affect: prediction from neuroticism, extraversion, and agreeableness. Journal of Personality and Social Psychology 75, 4 (1998), 1032--1046. https://doi.org/10.1037/0022-3514.75.4.1032Google ScholarCross Ref
- Henriette Cramer, Paloma de Juan, and Joel Tetreault. 2016. Sender-intended Functions of Emojis in US Messaging. In Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '16). ACM, New York, NY, USA, 504--509. https://doi.org/10.1145/2935334.2935370Google ScholarDigital Library
- Daniel Danner, Beatrice Rammstedt, Matthias Bluemke, Lisa Treiber, Sabrina Berres, Christopher Soto, and Oliver John. 2016. Die deutsche Version des Big Five Inventory 2 (BFI-2). In Zusammenstellung sozialwissenschaftlicher Items und Skalen. GESIS - Leibniz-Institut für Sozialwissenschaften, Mannheim, Germany, 19. https://doi.org/10.6102/zis247Google Scholar
- Boele De Raad. 2000. The Big Five Personality Factors: The psycholexical approach to personality. Hogrefe & Huber Publishers, Göttingen, Germany.Google Scholar
- Colin G DeYoung. 2014. Openness/Intellect: A dimension of personality reflecting cognitive exploration. In APA Handbook of Personality and Social Psychology: Personality Processes and Individual Differences, M. Mikulincer, P.R. Shaver, M.L. Cooper, and R.J. Larsen (Eds.). Vol. 4. American Psychological Association, Washington, DC, USA, 369--399. https://doi.org/10.1037/14343-017Google Scholar
- Ed Diener, ED Sandvik, William Pavot, and Frank Fujita. 1992. Extraversion and subjective well-being in a US national probability sample. Journal of Research in Personality 26, 3 (1992), 205--215. https://doi.org/10.1016/0092-6566(92)90039-7Google ScholarCross Ref
- Ben Eisner, Tim Rocktäschel, Isabelle Augenstein, Matko Bosnjak, and Sebastian Riedel. 2016. emoji2vec: Learning Emoji Representations from their Description. CoRR abs/1609.08359 (2016), 7. http://arxiv.org/abs/1609.08359Google Scholar
- Paul Ekman. 2005. Basic Emotions. John Wiley & Sons, Ltd, Hoboken, NJ, USA, Chapter 3, 45--60. https://doi.org/10.1002/0470013494.ch3Google Scholar
- Hans Jürgen Eysenck. 1994. Personality: Biological foundations. In The Neuropsychology of Individual Differences., P.A. Vernon (Ed.). Academic Press, San Diego, CA, US, 151--207. https://doi.org/10.1016/B978-0-12-718670-2.50011-6Google Scholar
- Lewis R Goldberg. 1981. Language and individual differences: The search for universals in personality lexicons. Review of personality and social psychology 2, 1 (1981), 141--165.Google Scholar
- Samuel D Gosling, Peter J Rentfrow, and William B Swann. 2003. A very brief measure of the Big-Five personality domains. Journal of Research in Personality 37, 6 (2003), 504--528. https://doi.org/10.1016/S0092-6566(03)00046-1Google ScholarCross Ref
- Rebecca E Grinter and Margery A Eldridge. 2001. y do tngrs luv 2 txt msg?. In Proceedings of the Seventh European Conference on Computer Supported Cooperative Work. Springer, Dordrecht, Netherlands, 219--238. https://doi.org/10.1007/0-306-48019-0_12Google ScholarDigital Library
- Gaël Guibon, Magalie Ochs, and Patrice Bellot. 2018. From Emoji Usage to Categorical Emoji Prediction. In 19th International Conference on Computational Linguistics and Intelligent Text Processing (CICLING 2018). Springer Lecture Notes in Computer Science, Switzerland, 10. https://hal-amu.archives-ouvertes.fr/hal-01871045Google Scholar
- Tianran Hu, Han Guo, Hao Sun, Thuy-vy Thi Nguyen, and Jiebo Luo. 2017. Spice up Your Chat: The Intentions and Sentiment Effects of Using Emoji. In International AAAI Conference on Web and Social Media. AAAI Publications, Palo Alto, CA, USA, 102--111. http://arxiv.org/abs/1703.02860Google Scholar
- Joshua J Jackson, Dustin Wood, Tim Bogg, Kate E Walton, Peter D Harms, and Brent W Roberts. 2010. What do conscientious people do? Development and validation of the Behavioral Indicators of Conscientiousness (BIC). Journal of Research in Personality 44, 4 (2010), 501--511. https://doi.org/10.1016/j.jrp.2010.06.005Google ScholarCross Ref
- Lauri A Jensen-Campbell and William G Graziano. 2001. Agreeableness as a moderator of interpersonal conflict. Journal of Personality 69, 2 (2001), 323--362. https://doi.org/10.1111/1467-6494.00148Google ScholarCross Ref
- Jialun "Aaron" Jiang, Casey Fiesler, and Jed R. Brubaker. 2018. 'The Perfect One': Understanding Communication Practices and Challenges with Animated GIFs. Proc. ACM Hum.-Comput. Interact. 2, CSCW, Article 80 (Nov. 2018), 20 pages. https://doi.org/10.1145/3274349Google Scholar
- Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufmann, Andrew Tomkins, Balint Miklos, Greg Corrado, Laszlo Lukacs, Marina Ganea, Peter Young, and Vivek Ramavajjala. 2016. Smart Reply: Automated Response Suggestion for Email. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '16). ACM, New York, NY, USA, 955--964. https://doi.org/10.1145/2939672.2939801Google ScholarDigital Library
- Linda K. Kaye, Helen J. Wall, and Stephanie A. Malone. 2016. "Turn that frown upside-down": A contextual account of emoticon usage on different virtual platforms. Computers in Human Behavior 60 (2016), 463--467. https://doi.org/10.1016/j.chb.2016.02.088Google ScholarDigital Library
- Ryan Kelly and Leon Watts. 2015. Characterising the Inventive Appropriation of Emoji as Relationally Meaningful in Mediated Close Personal Relationships. Paper presented at Experiences of Technology Appropriation: Unanticipated Users, Usage, Circumstances, and Design, Oslo, Norway, 20/09/15 - 20/09/15.Google Scholar
- Petra Kralj Novak, Jasmina Smailovia, Borut Sluban, and Igor Mozetia. 2015. Sentiment of Emojis. PLOS ONE 10, 12 (12 2015), 1--22. https://doi.org/10.1371/journal.pone.0144296Google Scholar
- Robert H Lengel and Richard L. Daft. 1984. An exploratory analysis of the relationship between media richness and managerial information processing. Technical Report. Texas A and M University. http://www.dtic.mil/dtic/tr/fulltext/u2/a143503.pdfGoogle Scholar
- Weijian Li, Yuxiao Chen, Tianran Hu, and Jiebo Luo. 2018. Mining the Relationship between Emoji Usage Patterns and Personality. In International AAAI Conference on Web and Social Media. AAAI Publications, Palo Alto, CA, USA, 4. http://arxiv.org/abs/1804.05143Google Scholar
- Richard Lippa. 1998. The nonverbal display and judgment of extraversion, masculinity, femininity, and gender diagnosticity: A lens model analysis. Journal of Research in Personality 32, 1 (1998), 80--107. https://doi.org/10.1006/jrpe.1997.2189Google ScholarCross Ref
- Xuan Lu, Wei Ai, Xuanzhe Liu, Qian Li, Ning Wang, Gang Huang, and Qiaozhu Mei. 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 (UbiComp '16). ACM, New York, NY, USA, 770--780. https://doi.org/10.1145/2971648.2971724Google ScholarDigital Library
- Davide Marengo, Fabrizia Giannotta, and Michele Settanni. 2017. Assessing personality using emoji: An exploratory study. Personality and Individual Differences 112 (2017), 74--78. https://doi.org/10.1016/j.paid.2017.02.037Google ScholarCross Ref
- Gerald Matthews, Ian J Deary, and Martha C Whiteman. 2003. Personality traits. Cambridge University Press, Cambridge, UK.Google Scholar
- Robert R McCrae. 2009. The Five-Factor Model of personality traits: consensus and controversy. In The Cambrdige handbook of personality psychology, P.J. Corr and G. Matthews (Eds.). Cambridge University Press, New York, NY, US, 148--161. https://doi.org/10.1017/CBO9780511596544.012Google Scholar
- Robert R McCrae and Paul T Costa Jr. 2008. A five-factor theory of personality. In Handbook of personality: Theory and research, O.P. John, R.W. Robins, and L.A. Pervin (Eds.). Vol. 3. The Guilford Press, New York, NY, USA, 159--181.Google Scholar
- Robert R McCrae and Oliver P John. 1992. An introduction to the five-factor model and its applications. Journal of Personality 60, 2 (1992), 175--215. https://doi.org/10.1111/j.1467-6494.1992.tb00970.xGoogle ScholarCross Ref
- J Murray McNiel and William Fleeson. 2006. The causal effects of extraversion on positive affect and neuroticism on negative affect: Manipulating state extraversion and state neuroticism in an experimental approach. Journal of Research in Personality 40, 5 (2006), 529--550. https://doi.org/10.1016/j.jrp.2005.05.003Google ScholarCross Ref
- Matthias R Mehl, Samuel D Gosling, and James W Pennebaker. 2006. Personality in its natural habitat: Manifestations and implicit folk theories of personality in daily life. Journal of Personality and Social Psychology 90, 5 (2006), 862--877. https://doi.org/10.1037/0022-3514.90.5.862Google ScholarCross Ref
- Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013. Distributed Representations of Words and Phrases and their Compositionality. In Advances in Neural Information Processing Systems 26, C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K. Q. Weinberger (Eds.). Curran Associates, Inc., Redhook, NY, USA, 3111--3119. https://arxiv.org/abs/1310.4546v1Google ScholarDigital Library
- Hannah Jean Miller, Daniel Kluver, Jacob Thebault-Spieker, Loren G Terveen, and Brent J Hecht. 2017. Understanding Emoji Ambiguity in Context: The Role of Text in Emoji-Related Miscommunication.. In International AAAI Conference on Web and Social Media. AAAI Publications, Palo Alto, CA, USA, 152--161.Google Scholar
- Hannah Jean Miller, Jacob Thebault-Spieker, Shuo Chang, Isaac Johnson, Loren Terveen, and Brent Hecht. 2017. "Blissfully happy" or "ready to fight": Varying Interpretations of Emoji. In International AAAI Conference on Web and Social Media. AAAI Publications, Palo Alto, CA, USA, 259--268.Google Scholar
- Robert B. O'Hara and D. Johan Kotze. 2010. Do not log-transform count data. Methods in Ecology and Evolution 1, 2 (2010), 118--122. https://doi.org/10.1111/j.2041-210X.2010.00021.xGoogle ScholarCross Ref
- James W Pennebaker, Ryan L Boyd, Kayla Jordan, and Kate Blackburn. 2015. The development and psychometric properties of LIWC2015. Technical Report. The University of Texas at Austin.Google Scholar
- Martha S. Perry and Ronald J. Werner-Wilson. 2011. Couples and Computer-Mediated Communication: A Closer Look at the Affordances and Use of the Channel. Family and Consumer Sciences Research Journal 40, 2 (2011), 120--134. https://doi.org/10.1111/j.1552-3934.2011.02099.xGoogle ScholarCross Ref
- Henning Pohl, Christian Domin, and Michael Rohs. 2017. Beyond Just Text: Semantic Emoji Similarity Modeling to Support Expressive Communication. ACM Trans. Comput.-Hum. Interact. 24, 1, Article 6 (March 2017), 42 pages. https://doi.org/10.1145/3039685Google ScholarDigital Library
- Ruth Rettie. 2009. Mobile Phone Communication: Extending Goffman to Mediated Interaction. Sociology 43, 3 (2009), 421--438. https://doi.org/10.1177/0038038509103197Google ScholarCross Ref
- David Rodrigues, Diniz Lopes, Marilia Prada, Dominic Thompson, and Margarida V. Garrido. 2017. A frown emoji can be worth a thousand words: Perceptions of emoji use in text messages exchanged between romantic partners. Telematics and Informatics 34, 8 (2017), 1532--1543. https://doi.org/10.1016/j.tele.2017.07.001Google ScholarDigital Library
- Christopher J Soto and Oliver P John. 2017. The next Big Five Inventory (BFI-2): Developing and assessing a hierarchical model with 15 facets to enhance bandwidth, fidelity, and predictive power. Journal of Personality and Social Psychology 113, 1 (2017), 117--143. https://doi.org/10.1037/pspp0000096Google ScholarCross Ref
- Clemens Stachl and Markus Bühner. 2015. Show me how you drive and I'll tell you who you are: Recognizing gender using automotive driving parameters. Procedia Manufacturing 3 (2015), 5587--5594. https://doi.org/10.1016/j.promfg.2015.07.743Google ScholarCross Ref
- Clemens Stachl, Sven Hilbert, Jiew-Quay Au, Daniel Buschek, Alexander De Luca, Bernd Bischl, Heinrich Hussmann, and Markus Bühner. 2017. Personality Traits Predict Smartphone Usage. European Journal of Personality 31, 6 (2017), 701--722. https://doi.org/10.1002/per.2113Google ScholarCross Ref
- Statcounter. 2018. Mobile Operating System Market Share Worldwide. http://gs.statcounter.com/os-market-share/mobile/worldwide, last accessed: 19-01-28.Google Scholar
- Statista. 2019. Most popular global mobile messenger apps as of October 2018, based on number of monthly active users (in millions). https://www.statista.com/statistics/258749/most-popular-global-mobile-messenger-apps/, last accessed: 19-01-28.Google Scholar
- SwiftKey. 2015. SwiftKey Emoji Report. Technical Report. SwiftKey. http://www.scribd.com/doc/262594751/SwiftKey-Emoji-Report, last accessed: 19/01/06.Google Scholar
- Ying Tang and Khe Foon Hew. 2018. Emoticon, Emoji, and Sticker Use in Computer-Mediated Communications: Understanding Its Communicative Function, Impact, User Behavior, and Motive. In New Media for Educational Change, Liping Deng, Will W. K. Ma, and Cheuk Wai Rose Fong (Eds.). Springer, Singapore, 191--201. https://doi.org/10.1007/978-981-10-8896-4_16Google Scholar
- Channary Tauch and Eiman Kanjo. 2016. The Roles of Emojis in Mobile Phone Notifications. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (UbiComp '16). ACM, New York, NY, USA, 1560--1565. https://doi.org/10.1145/2968219.2968549Google ScholarDigital Library
- Crispin Thurlow and Alex Brown. 2003. Generation Txt? The sociolinguistics of young people's text-messaging. Discourse analysis online 1, 1 (2003), 30.Google Scholar
- Garreth W. Tigwell and David R. Flatla. 2016. Oh That's What You Meant!: Reducing Emoji Misunderstanding. In Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct (MobileHCI '16). ACM, New York, NY, USA, 859--866. https://doi.org/10.1145/2957265.2961844Google ScholarDigital Library
- Joseph B Walther. 2011. Theories of computer-mediated communication and interpersonal relations. In The handbook of interpersonal communication. Sage Publications Ltd., Thousand Oaks, CA, USA, Chapter 4, 443--479.Google Scholar
- Joseph B. Walther and Kyle P. D'Addario. 2001. The Impacts of Emoticons on Message Interpretation in Computer-Mediated Communication. Social Science Computer Review 19, 3 (2001), 324--347. https://doi.org/10.1177/089443930101900307Google ScholarCross Ref
- Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, and Derek Doran. 2017. A Semantics-based Measure of Emoji Similarity. In Proceedings of the International Conference on Web Intelligence (WI '17). ACM, New York, NY, USA, 646--653. https://doi.org/10.1145/3106426.3106490Google ScholarDigital Library
- Dean Withey. 2017. 2017 Chatbot Survey. https://insights.ubisend.com/2017-chatbot-report, last accessed: 19-01-31.Google Scholar
- Lingling Xu, Cheng Yi, and Yunjie Xu. 2007. Emotional expression online: The impact of task, relationship and personality perception on emoticon usage in instant messenger. In Pacific Asia Conference on Information Systems. AIS, 15.Google Scholar
- Rui Zhou, Jasmine Hentschel, and Neha Kumar. 2017. Goodbye Text, Hello Emoji: Mobile Communication on WeChat in China. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17). ACM, New York, NY, USA, 748--759. https://doi.org/10.1145/3025453.3025800Google ScholarDigital Library
Index Terms
- Understanding Emoji Interpretation through User Personality and Message Context
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