An official website of the United States government
Social media has been at the center of discussions about political polarization in the United States. However, scholars are actively debating both the scale of political polarization online, and how important online polarization is to the offline world. One question at the center of this debate is what interactions across parties look like online, and in particular 1) whether increasing the number of such interactions is likely to increase or reduce polarization, and 2) what technological affordances may make it more likely that these cross-party interactions benefit, rather than detract from, existing political challenges. The present work aims to provide insights into the latter; that is, we focus on providing a better understanding of how a set of 400,000 partisan users on a particular social media platform, Twitter, used the platform's affordances to interact within and across parties in a large dataset of tweets about COVID in 2021. Our findings suggest that Republican use of cross-party interaction were both more potent and potentially more strategic during COVID, that cross-party interaction was driven heavily by a small set of users and conversations, and that there exist non-obvious indirect pathways to cross-party exposure when different modes of interaction are chained together (especially retweets of quotes). These findings have implications beyond Twitter, we believe, in understanding how affordances of platforms can help to shape partisan exposure and interaction.
more »
« less
To Reply or to Quote: Comparing Conversational Framing Strategies on Twitter
Social media platform affordances allow users to interact with content and with each other in diverse ways. For example, on Twitter,1users can like, reply, retweet, or quote another tweet. Though it’s clear that these different features allow various types of interactions, open questions remain about how these different affordances shape the conversations. We examine how two similar, but distinct conversational features on Twitter — specifically reply vs. quote — are used differently. Focusing on the polarized discourse around Robert Mueller’s congressional testimony in July 2019, we look at how these features are employed in conversations between politically aligned and opposed accounts. We use a mixed methods approach, employing grounded qualitative analysis to identify the different conversational and framing strategies salient in that discourse and then quantitatively analyzing how those techniques differed across the different features and political alignments. Our research (1) demonstrates that the quote feature is more often used to broadcast and reply is more often used to reframe the conversation; (2) identifies the different framing strategies that emerge through the use of these features when engaging with politically aligned vs. opposed accounts; (3) discusses how reply and quote features may be re-designed to reduce the adversarial tone of polarized conversations on Twitter-like platforms.
more »
« less
- PAR ID:
- 10522619
- Publisher / Repository:
- Association for Computing Machinery
- Date Published:
- Journal Name:
- ACM Journal on Computing and Sustainable Societies
- Volume:
- 2
- Issue:
- 1
- ISSN:
- 2834-5533
- Page Range / eLocation ID:
- 1 to 27
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
The Language, Culture, and Knowledge-building through Science (LaCuKnoS) project tests and refines a model of science teaching and learning that brings together current research on the role of language in science communication, the role of cultural and community connections in science engagement, and the ways people apply science knowledge to their daily decision making. One key component of the model brings families together as co-learners and co-teachers through family learning experiences. We describe our work to promote more robust family conversations about science in our lives within an existing research practice partnership, using a two-tiered qualitative conversational analysis to compare the family conversations that result from three family engagement models: (a) family science festivals; (b) family science workshops; and (c) family science home learning. More specifically, this paper addresses the question: How do families describe and evaluate science in their lives and communities during family conversations that occur during each of these three engagement models? Discourse analysis using the appraisal dimension of systemic functional linguistics highlights the affective components of families evaluating science in their lives, as well as how each model provided unique affordances for different communicative goals. These findings are used to propose a set of design principles to guide the continued exploration of community-sustaining and family-centric models of family engagement as a key strategy for broadening science participation.more » « less
-
Conversational systems typically focus on functional tasks such as scheduling appointments or creating todo lists. Instead we design and evaluate SlugBot (SB), one of 8 semifinalists in the 2018 AlexaPrize, whose goal is to support casual open-domain social inter-action. This novel application requires both broad topic coverage and engaging interactive skills. We developed a new technical approach to meet this demanding situation by crowd-sourcing novel content and introducing playful conversational strategies based on storytelling and games. We collected over 10,000 conversations during August 2018 as part of the Alexa Prize competition. We also conducted an in-lab follow-up qualitative evaluation. Over-all users found SB moderately engaging; conversations averaged 3.6 minutes and involved 26 user turns. However, users reacted very differently to different conversation subtypes. Storytelling and games were evaluated positively; these were seen as entertaining with predictable interactive structure. They also led users to impute personality and intelligence to SB. In contrast, search and general Chit-Chat induced coverage problems; here users found it hard to infer what topics SB could understand, with these conversations seen as being too system-driven. Theoretical and design implications suggest a move away from conversational systems that simply provide factual information. Future systems should be designed to have their own opinions with personal stories to share, and SB provides an example of how we might achieve this.more » « less
-
Abstract Citizen-generated counter speech is a promising way to fight hate speech and promote peaceful, non-polarized discourse. However, there is a lack of large-scale longitudinal studies of its effectiveness for reducing hate speech. To this end, we perform an exploratory analysis of the effectiveness of counter speech using several different macro- and micro-level measures to analyze 180,000 political conversations that took place on German Twitter over four years. We report on the dynamic interactions of hate and counter speech over time and provide insights into whether, as in ‘classic’ bullying situations, organized efforts are more effective than independent individuals in steering online discourse. Taken together, our results build a multifaceted picture of the dynamics of hate and counter speech online. While we make no causal claims due to the complexity of discourse dynamics, our findings suggest that organized hate speech is associated with changes in public discourse and that counter speech—especially when organized—may help curb hateful rhetoric in online discourse.more » « less
-
Bots are social media accounts that automate interaction with other users, and they are active on the StrongerIn-Brexit conversation happening over Twitter. These automated scripts generate content through these platforms and then interact with people. Political bots are automated accounts that are particularly active on public policy issues, elections, and political crises. In this preliminary study on the use of political bots during the UK referendum on EU membership, we analyze the tweeting patterns for both human users and bots. We find that political bots have a small but strategic role in the referendum conversations: (1) the family of hashtags associated with the argument for leaving the EU dominates, (2) different perspectives on the issue utilize different levels of automation, and (3) less than 1 percent of sampled accounts generate almost a third of all the messages.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3625680
