Don't Let Me Be Misunderstood: Comparing Intentions and Perceptions in Online Discussions

Discourse involves two perspectives: a person's intention in making an utterance and others' perception of that utterance. The misalignment between these perspectives can lead to undesirable outcomes, such as misunderstandings, low productivity and even overt strife. In this work, we present a computational framework for exploring and comparing both perspectives in online public discussions. We combine logged data about public comments on Facebook with a survey of over 16,000 people about their intentions in writing these comments or about their perceptions of comments that others had written. Unlike previous studies of online discussions that have largely relied on third-party labels to quantify properties such as sentiment and subjectivity, our approach also directly captures what the speakers actually intended when writing their comments. In particular, our analysis focuses on judgments of whether a comment is stating a fact or an opinion, since these concepts were shown to be often confused. We show that intentions and perceptions diverge in consequential ways. People are more likely to perceive opinions than to intend them, and linguistic cues that signal how an utterance is intended can differ from those that signal how it will be perceived. Further, this misalignment between intentions and perceptions can be linked to the future health of a conversation: when a comment whose author intended to share a fact is misperceived as sharing an opinion, the subsequent conversation is more likely to derail into uncivil behavior than when the comment is perceived as intended. Altogether, these findings may inform the design of discussion platforms that better promote positive interactions.Comment: Proceedings of The Web Conference (WWW) 202

Incivility

Incivility is considered a significant challenge for democratic discourse and has been the subject of many studies in a variety of contexts. Although political incivility has a long research tradition, and scholarly attention toward the phenomenon has increased with the advance of social media, there is academic controversy regarding the concept and normative implications of incivility in political contexts. This chapter provides an overview of different incivility approaches in the extant literature, discusses key challenges in incivility research, and outlines normative implications. Further, we suggest future directions for incivility research and argue why an integrative, multidimensional concept of incivility offers great potential for incivility research in the field of political (online) communication

Platformization hate. Patterns and algorithmic bias of verbal violence on social media

The paper presented is an analysis of the Hate Speech of tweets during the implementation of the EU's Digital Covid Certificate policy. The work starts from the assumption that Hate Speech is an often "submerged" phenomenon because it also includes some forms recognized as "incivility." Therefore, there are two research questions: the first asks what are the new categories of "hate" that emerge in the EU Digital Covid Certificate policy debate, while the second questions the methodological implications on the use of algorithms in detecting the phenomenon. The results we arrived at are, from a substantive point of view, of good interest because they show us how it is possible to witness a new kind of online hatred. However, the disagreements we encountered in constructing an unambiguous definition of HS for the supervised algorithm leave open many questions. Among them is the fact that the differences between HS, incivility, and even freedom of expression can be very small. In the context of large social platforms, where the criteria of the algorithm are not always explicit and are also the policies of the platform, this could be a proble

Challenges and perspectives of hate speech research

This book is the result of a conference that could not take place. It is a collection of 26 texts that address and discuss the latest developments in international hate speech research from a wide range of disciplinary perspectives. This includes case studies from Brazil, Lebanon, Poland, Nigeria, and India, theoretical introductions to the concepts of hate speech, dangerous speech, incivility, toxicity, extreme speech, and dark participation, as well as reflections on methodological challenges such as scraping, annotation, datafication, implicity, explainability, and machine learning. As such, it provides a much-needed forum for cross-national and cross-disciplinary conversations in what is currently a very vibrant field of research

Hate Cannot Drive out Hate: Forecasting Conversation Incivility following Replies to Hate Speech

User-generated replies to hate speech are promising means to combat hatred, but questions about whether they can stop incivility in follow-up conversations linger. We argue that effective replies stop incivility from emerging in follow-up conversations - replies that elicit more incivility are counterproductive. This study introduces the task of predicting the incivility of conversations following replies to hate speech. We first propose a metric to measure conversation incivility based on the number of civil and uncivil comments as well as the unique authors involved in the discourse. Our metric approximates human judgments more accurately than previous metrics. We then use the metric to evaluate the outcomes of replies to hate speech. A linguistic analysis uncovers the differences in the language of replies that elicit follow-up conversations with high and low incivility. Experimental results show that forecasting incivility is challenging. We close with a qualitative analysis shedding light into the most common errors made by the best model.Comment: The 18th International AAAI Conference on Web and Social Media (ICWSM 2024) Accepte

Incivility on Popular Politics and News Subreddits: An Analysis of In-groups, Community Guidelines and Relationships with Social Media Engagement

Political and news subreddits are individualistic as it pertains to the incivility we might expect them to exhibit; some have clear in-group members, and all have varying degrees of content moderation policies. We sample submissions (n = 127,870) and comments (n = 2,576,049) from 20 of the most popular news and politics subreddits from June 4th, 2021, to June 4th, 2022. All subreddits appear to be mostly civil, with incivility most commonly occurring in comments. When incivility occurs, it tends to take on less-severe forms including insults, profanity, and general toxicity. Subreddits with with clear political in-groups did exhibit more insults, toxicity, profanity, and identity-based attacks. The more complex a subreddit’s moderation policies, the less incivility was observed. Finally, uncivil submissions do result in a mild increase in engagement, but given the overall low prevalence of incivility observed, it appears not to be integral to a subreddit’s overall engagement

Is Aggression Contagious Online? A Case of Swearing on Donald Trump’s Campaign Videos on YouTube

This study explores whether aggressive text-based interactions in social media are contagious. In particular, we examine swearing behaviour of YouTube commentators in response to videos and comments posted on the official Donald Trump’s campaign channel. Our analysis reveals the presence of mimicry of verbal aggression. Specifically, swearing in a parent comment is significantly and positively associated with the likelihood and intensity of swearing in subsequent ‘children’ comments. The study also confirms that swearing is not solely a product of an individual speech habit but also a spreadable social practice. Based on the findings, we conclude that aggressive emotional state can be contagious through textual mimicry.

Social media, political polarization, and political disinformation: a review of the scientific literature

The following report is intended to provide an overview of the current state of the literature on the relationship between social media; political polarization; and political “disinformation,” a term used to encompass a wide range of types of information about politics found online, including “fake news,” rumors, deliberately factually incorrect information, inadvertently factually incorrect information, politically slanted information, and “hyperpartisan” news. The review of the literature is provided in six separate sections, each of which can be read individually but that cumulatively are intended to provide an overview of what is known — and unknown — about the relationship between social media, political polarization, and disinformation. The report concludes by identifying key gaps in our understanding of these phenomena and the data that are needed to address them

Social media, political polarization, and political disinformation: a review of the scientific literature

The following report is intended to provide an overview of the current state of the literature on the relationship between social media; political polarization; and political “disinformation,” a term used to encompass a wide range of types of information about politics found online, including “fake news,” rumors, deliberately factually incorrect information, inadvertently factually incorrect information, politically slanted information, and “hyperpartisan” news. The review of the literature is provided in six separate sections, each of which can be read individually but that cumulatively are intended to provide an overview of what is known — and unknown — about the relationship between social media, political polarization, and disinformation. The report concludes by identifying key gaps in our understanding of these phenomena and the data that are needed to address them