research-article

Diversity from Emojis and Keywords in Social Media

Authors:

Melanie Swartz,

William KennedyAuthors Info & Claims

SMSociety'20: International Conference on Social Media and Society

Pages 92 - 100

https://doi.org/10.1145/3400806.3400818

Published: 22 July 2020 Publication History

Abstract

Social media is a popular source for political communication and user engagement around social and political issues. While the diversity of the population participating in social and political events in person are often considered for social science research, measuring the diversity representation within online communities is not a common part of social media analysis. This paper attempts to fill that gap and presents a methodology for labeling and analyzing diversity in a social media sample based on emojis and keywords associated with gender, skin tone, sexual orientation, religion, and political ideology. We analyze the trends of diversity related themes and the diversity of users engaging in the online political community during the leadup to the 2018 U.S. midterm elections. Our results reveal patterns along diversity themes that otherwise would have been lost in the volume of content. Further, the diversity composition of our sample of online users rallying around political campaigns was similar to those measured in exit polls on election day. The diversity language model and methodology for diversity analysis presented in this paper can be adapted to other languages and applied to other research domains to provide social media researchers a valuable lens to identify the diversity of voices and topics of interest for the less-represented populations participating in an online social community.

References

[1]

Adam Badaway, Kristina Lerman, and Emilio Ferrara. 2019. Who falls for online political manipulation? In Proceedings of the 2019 World Wide Web Conference, May 13-17, 2019, San Francisco, CA, 162-168.

Digital Library

[2]

Pablo Barberá. 2016. Less is more? How demographic sample weights can improve public opinion estimates based on Twitter data. Working Paper, New York University.

[3]

Pablo Barberá and Thomas Zeitzoff. 2018. The new public address system: Why do world leaders adopt social media? International Studies Quarterly, 62, 1, 121-130.

[4]

Francesco Barbieri and Jose Camacho-Collados. 2018. How gender and skin tone modifiers affect emoji semantics in Twitter. In Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics (SEM18), June 5-6, 2018, New Orleans, Louisiana, 101-106.

[5]

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 2016 ACM on Multimedia Conference (MM’16), October 15-19, 2016, Amsterdam, The Netherlands, 531-535.

Digital Library

[6]

Grant Blank and Christoph Lutz. 2017. Representativeness of social media in Great Britain: Investigating Facebook, LinkedIn, Twitter, Pinterest, Google+, and Instagram. American Behavioral Scientist, 61, 741-756.

[7]

Leticia Bode and Kajsa E. Dalrymple. 2016. Politics in 140 characters or less: Campaign communication, network interaction, and political participation on Twitter. Journal of Political Marketing, 15, 4, 311-332.

[8]

Abhijnan Chakraborty, Johnnatan Messias, Fabricio Benevenuto, Saptarshi Ghosh, Niloy Ganguly, and Krishna P. Gummadi. 2017. Who makes trends? Understanding demographic biases in crowdsourced recommendations. In Eleventh International Conference on Web and Social Media (ICWSM-17), May 16-18, 2017, Montréal, Québec, Canada, 22-31.

[9]

Zhenpeng Chen, Xuan Lu, Wei Ai, Huoran Li, Qiaozhu Mei, and Xuanhe 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), April 23-27, 2018, Lyon, France, 763-772.

Digital Library

[10]

Andrew Crooks, Arie Croitoru, Anthony Stefanidis, and Jacek Radzikowski. 2013. #Earthquake: Twitter as a distributed sensor system. Transactions in GIS, 17, 1, 124-147.

[11]

Elizabeth Culliford. 2019. Twitter makes global changes to comply with privacy laws. Reuters, December 2, 2019. https://www.reuters.com/article/us-twitter-privacy/twitter-makes-global-changes-to-comply-with-privacy-laws-idUSKBN1Y622J.

[12]

Ashok Deb, Luca Luceri, Adam Badaway, and Emilio Ferrara. 2019. Perils and challenges of social media and election manipulation analysis: The 2018 US midterms. In Companion Proceedings of the 2019 World Wide Web Conference (WWW’19), May 13-17, 2019, San Francisco, CA, 237-247.

Digital Library

[13]

Carroll Doherty, Jocelyn Kiley, and Olivia O'Hea. 2018. Wide gender gap, growing educational divide in voters’ party identification. Pew Research Center.

[14]

Giulia Donato and Patrizia Paggio. 2017. Investigating redundancy in emoji use: Study on a Twitter based corpus. In Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA 2017), September 8, 2017, Copenhagen, Denmark, 118-126.

[15]

Maeve Duggan and Joanna Brenner. 2013. The demographics of social media users, 2012. Pew Research Center.

[16]

Bjarke Felbo, Alan Mislove, Anders Søgaard, Iyad Rahwan, and Sune Lehmann. 2017. Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion, and sarcasm. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP 2017), September 7-11, 2017, Copenhagen, Denmark, 1615-1625.

[17]

Lauren Gawne, and Gretchen McCulloch. 2019. Emoji as digital gestures. Language@ Internet, 17, 2. http://nbn-resolving.de/urn:nbn:de:0009-7-48882

[18]

Salvatore Giorgi, Veronica Lynn, Sandra Matz, Lyle Ungar, Hansen Andrew Schwartz. 2019. Correcting sociodemographic selection biases for accurate population prediction from social media. rXiv preprint arXiv:1911.03855.

[19]

Sandra Halperin and Oliver Heath. 2020. Political research: Methods and practical skills. Oxford University Press, USA, 2020.

[20]

Eszter Hargittai. 2018. Potential biases in big data: Omitted voices on social media. Social Science Computer Review, 38, 1, 10-24.

Digital Library

[21]

Susan C. Herring and Ashley R. Dainas. 2018. Receiver interpretations of emoji functions: A gender perspective. In1st International Workshop on Emoji Understanding and Applications in Social Media (Emoji 2018), June 25, 2018, Stanford, CA, USA.

[22]

Jaigris Hodson and Brigitte Petersen. 2019. Diversity in Canadian election-related Twitter discourses: Influential voices and the media logic of #elxn42 and #cdnpoli hashtags. Journal of Information Technology & Politics, 16, 3, 307-323.

[23]

Adam Hughes and Nida Asheer. 2019. National politics on Twitter: Small share of U.S. adults produce majority of tweets. Pew Research Center.

[24]

Kyriaki Kalimeri, Mariano G. Beiró, Matteo Delfino, Robert Raleigh, and Ciro Cattuto. 2019. Predicting demographics, moral foundations, and human values from digital behaviours. Computers in Human Behavior, 92, 428-445.

Digital Library

[25]

Dijana Kosmajac and Vlado Keselj. 2019. Twitter bot detection using diversity measures. In Proceedings of the 3rd International Conference on Natural Language and Speech Processing, September 12-13, 2019, Trento, Italy, 1-8.

[26]

Nikola Ljubešić and Darja Fišer. 2016. A global analysis of emoji usage. In Proceedings of the 10th Web as Corpus Workshop (WAC-X 2016), August 12, 2016, Berlin, Germany, 82-89.

[27]

Hannah Miller, Daniel Kluver, Jacob Thebault-Spieker, Loren Terveen, and Brent Hecht. 2017. Understanding emoji ambiguity in context: The role of text in emoji-related miscommunication. In Eleventh International Conference on Web and Social Media (ICWSM-17), May 16-18, 2017, Montréal, Québec, Canada, 152-161.

[28]

Alan Miller, Sune Lehmann, Yong-Yeol Ahn, Jukka-Pekka Onnela, and J. Niels Rosenquist. 2011. Understanding the demographics of Twitter users. In Fifth International Conference on Web and Social Media (ICWSM-11), July 17-21, 2011, Barcelona, Spain, 554-557.

[29]

Ahmed Mourad, Falk Scholer, Walid Magdy, and Mark Sanderson. 2019. A practical guide for the effective evaluation of Twitter user geolocation. ACM Transactions on Social Computing, 2, 3, 1-23.

Digital Library

[30]

Nao Na'aman, Hannah Provenza, and Orion Montoya. 2017. Varying linguistic purposes of emoji in (Twitter) context. In ACL 2017, Student Research Workshop, July 30-August 4, Vancouver, Canada, 136-141.

[31]

Daniel Preoţiuc-Pietro and Lyle Ungar. 2018. User-level race and ethnicity predictors from Twitter text. In Proceedings of the 27th International Conference on Computational Linguistics (COLING-18), August 20-26, 2018, Santa Fe, New Mexico, USA, 1534-1545.

[32]

Alexander Robertson, Walid Magdy, and Sharon Goldwater. 2018. Self-representation on Twitter using emoji skin color modifiers. In 12th International Conference on Web and Social Media (ICWSM-18), June 25-28, 2018, Stanford, CA, USA, 680-683.

[33]

Jonathon Schuldt, and Adam Pearson. 2016. The role of race and ethnicity in climate change polarization: evidence from a U.S. national survey experiment. Climatic Change, 136, 495–505.

[34]

Elisa Shearer and Jeffrey Gottfried. 2017. News use across social media platforms 2017. Pew Research Center.

[35]

Luke Sloan, Jeffrey Morgan, William Housley, Matthew Williams, Adam Edwards, Pete Burnap, and Omer Rana. 2013. Knowing the tweeters: Deriving sociologically relevant demographics from Twitter. Sociological Research Online, 18, 3, 1-11.

[36]

Felipe Bonow Soares, Raquel Recuero, and Gabriela Zago. 2019. Asymmetric polarization on Twitter and the 2018 Brazilian presidential elections. In Proceedings of the 10th International Conference on Social Media and Society, July 19-21, 2019, Toronto, Ontario, Canada, 67-76.

Digital Library

[37]

Joanna Sterling, John T. Jost, and Richard Bonneau. 2020. Political psycholinguistics: A comprehensive analysis of the language habits of liberal and conservative social media users. Journal of Personality and Social Psychology, 18, 4, 805-834.

[38]

Stefan Stieglitz, Milad Mirbabaie, Björn Ross, and Christoph Neuberger. 2018. Social media analytics–Challenges in topic discovery, data collection, and data preparation. International Journal of Information Management, 39, 156-168.

[39]

Sebastien Stier, Arnim Bleier, Haiko Lietz, and Markus Strohmaier. 2018. Election campaigning on social media: Politicians, audiences, and the mediation of political communication on Facebook and Twitter. Political Communication, 35, 1, 50-74.

[40]

Melanie Swartz and Andrew Crooks. 2020. Comparison of emoji use in names, profiles, and tweets. In IEEE 14th International Conference on Semantic Computing (ICSC), San Diego, CA, USA, 2020, 375-380.

[41]

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), September 6-9, 2016, Florence, Italy, 859-866.

[42]

Alec Tyson. 2018. The 2018 midterm vote: Divisions by race, gender, and education. Pew Research Center.

[43]

Unicode Emoji. 2018. In Unicode Technical Standard #51. Unicode.org.

[44]

Maurice Vergeer, Liesbeth Hermans, and Steven Sams. 2013. Online social networks and micro-blogging in political campaigning: The exploration of a new campaign tool and a new campaign style. Party Politics, 19, 3, 477-501.

[45]

Xiaoyi Yuan and Andrew T. Crooks. 2018. Examining online vaccination discussion and communities in Twitter. In Proceedings of the 9th International Conference on Social Media and Society, July 18-20, 2018, Copenhagen, Denmark, 197-206.

Digital Library

Cited By

Murata ETago KJin Q(2023)Investigating the Factors to Improve Discrimination of the Desire for Approval in Tweets by Incorporating Dependency AnalysisHCI International 2023 – Late Breaking Papers10.1007/978-3-031-48044-7_23(316-325)Online publication date: 21-Nov-2023
https://doi.org/10.1007/978-3-031-48044-7_23
Barinaga-López BPuente-Bienvenido HNavarro Newball A(2022)A systematic review of trends and gaps in the production of scientific knowledge on the sociopolitical impacts of emojis in computer-mediated communicationCogent Social Sciences10.1080/23311886.2022.21510968:1Online publication date: 12-Dec-2022
https://doi.org/10.1080/23311886.2022.2151096
Belimova PZhalimova SDzhumagulova A(2020)Development of a Universal Pictographic Language KeyboardProceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 210.51130/graphicon-2020-2-3-83(paper83-1-paper83-10)Online publication date: 17-Dec-2020
https://doi.org/10.51130/graphicon-2020-2-3-83

Recommendations

Social media and political participation: are facebook, twitter and YouTube democratizing our political systems?
ePart'11: Proceedings of the Third IFIP WG 8.5 international conference on Electronic participation

This paper presents the results of a literature review in regard to Social Media and participation. Besides that, to understand the meaning and impact of Social Media on elections, we show field results from the 2010 and 2011 elections in the ...
What matters most in the responses to political campaign posts on social media: The candidate, message frame, or message format?
Abstract
The responses of social media users to politicians' different content strategies have tremendous implications for election campaigns. However, the identification of the factors that influence social media users' responses remains a ...
Highlights
- A new method is proposed to automatically select correlated variables.
- Social ...
Social media and online political participation

Blog use and SNS use are positively related to online political participation.Like-minded exposure mediates the relationship between blog use and political participation.Cross-cutting exposure mediates the relationship between SNS use and political ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

SMSociety'20: International Conference on Social Media and Society

July 2020

317 pages

ISBN:9781450376884

DOI:10.1145/3400806

Editors:
Anatoliy Gruzd
Ryerson University in Canada
,
Philip Mai
Ryerson University in Canada
,
Raquel Recuero
Federal University of Pelotas and Federal University of Rio Grande do Sul in Brazil
,
Ángel Hernández-García
Universidad Politécnica de Madrid in Spain
,
Chei Sian Lee
Nanyang Technological University in Singapore
,
James Cook
University of Maine at Augusta in the United States
,
Jaigris Hodson
Royal Roads University in Canada
,
Bree McEwan
DePaul University in the United States
,
Jill Hopke
DePaul University in the United States

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 July 2020

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

SMSociety'20

SMSociety'20: International Conference on Social Media and Society

July 22 - 24, 2020

ON, Toronto, Canada

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
356
Total Downloads

Downloads (Last 12 months)35
Downloads (Last 6 weeks)1

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Murata ETago KJin Q(2023)Investigating the Factors to Improve Discrimination of the Desire for Approval in Tweets by Incorporating Dependency AnalysisHCI International 2023 – Late Breaking Papers10.1007/978-3-031-48044-7_23(316-325)Online publication date: 21-Nov-2023
https://doi.org/10.1007/978-3-031-48044-7_23
Barinaga-López BPuente-Bienvenido HNavarro Newball A(2022)A systematic review of trends and gaps in the production of scientific knowledge on the sociopolitical impacts of emojis in computer-mediated communicationCogent Social Sciences10.1080/23311886.2022.21510968:1Online publication date: 12-Dec-2022
https://doi.org/10.1080/23311886.2022.2151096
Belimova PZhalimova SDzhumagulova A(2020)Development of a Universal Pictographic Language KeyboardProceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 210.51130/graphicon-2020-2-3-83(paper83-1-paper83-10)Online publication date: 17-Dec-2020
https://doi.org/10.51130/graphicon-2020-2-3-83

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Figures

Tables

Media

View Table of Conten