Wednesday, July 22, 2020

Diversity from Emojis and Keywords in Social Media

Building on our initial work on emojis  use and and how one can carry out a systematic comparison of emojis across individual user profiles and communication patterns within social media, we have a new paper entitled: "Diversity from Emojis and Keywords in Social Media" which was presented at the 11th International Conference on Social Media and Society

In the paper we present a novel method using a diversity language model to associate diversity related attributes to social media user accounts and content by analyzing the emojis and keywords used (in this case from Twitter). We used this diversity language model to shed light on the groups of social media users and content with similar diversity attributes related to American politics (specifically the 2018 U.S. midterm elections). Our results revealed topics of interest and patterns of social media engagement across political lines among the diverse populations that otherwise would not have been apparent if we only analyzed the key political campaign phrases and slogans (i.e. “Blue Wave” and “Make America Great Again”) without taking diversity into account.

For interested readers, below we provide the abstract to the paper along with some figures from the paper. These include our workflow for diversity analysis of social media content, a high level overview of our diversity language model. These are followed by some of our results. Specifically the presence of diversity keywords and emojis in user profiles, and the composition of users in our collection based on gender for two political campaigns. If this peaks you interest as the conferce was virtual we have also prepared a short movie of the paper. While at the bottom of the post you find the full reference to the paper along with a link to the paper itself.

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 lead up 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.

Keywords: Social media, emoji, diversity, elections, political campaigns
Workflow for diversity analysis of social media content
Diversity Language Model
Presence of diversity keywords and emojis in user profiles
Composition of users in our collection based on gender for two political campaigns

Full Reference:

Swartz, M., Crooks, A.T. and Kennedy, W.G. (2020), Diversity from Emojis and Keywords in Social Media, in Gruzd, A., Mai, P., Recuero, R., Hernández-García, A., Lee, C.S., Cook, J., Hodson, J., McEwan, B and Hopke, J. (eds.), Proceedings of the 11th International Conference on Social Media & Society, Toronto, Canada, pp 92-100. (pdf)