“Social emotion” in text mining refers to the emotion experienced by the reader exposed to a text, as opposed to the emotion conveyed from the author’s perspective. Mining the cause of social emotion from text is a new challenging task with a wide range of applications, but its progress is hindered by the lack of annotated datasets. In this paper, we release the first English dataset for social emotion cause. The dataset is based on a well-established corpus of Facebook posts, and it was annotated through a crowdsourcing experiment. Together with the dataset, we provide two baseline models to be used as benchmarks for future studies.

Social emotion prediction is concerned with the prediction of the reader’s emotion when exposed to a text. In this paper, we propose a transfer learning approach to social emotion prediction, where the source task is writer’s emotion prediction, an area in which models are advanced due to the rich literature and availability of large and high-quality training datasets. We utilized a pre-trained writer’s emotion prediction model to predict the writer’s emotion in comments, then we aggregated the emotions and trained a classifier to predict social emotion for posts. Results show that pre-trained models for writer’s emotion prediction can improve the prediction of social emotion. Furthermore, we demonstrate that our proposed model outperforms popular models in terms of F1-score and performs similarly to the best model in terms of Acc@1.

Motivated by the effects of the filter bubble and echo chamber phenomena on social media, we developed a smart home device, Spkr, that unpredictably "pushes" socio-political discussion topics into the home. The device utilised trending Twitter discussions, categorised by their socio-political alignment, to present people with a purposefully assorted range of viewpoints. We deployed Spkr in 10 homes for 28 days with a diverse range of participants and interviewed them about their experiences. Our results show that Spkr presents a novel means of combating selective exposure to socio-political issues, providing participants with identifiably diverse viewpoints. Moreover, Spkr acted as a conversational prompt for discussion within the home, initiating collective processes and engaging those who would not often be involved in political discussions. We demonstrate how smart home assistants can be used as a catalyst for provocation by altering and pluralising political discussions within households.

Public commentary related to reality TV can be overwhelmed by thoughtless reactions and negative sentiments, which often problematically reinforce the cultural stereotyping typically employed in such media. We describe the design, and month-long evaluation, of a mobile "second-screening" application, Screenr, which uses co-voting and live textual tagging to encourage more critical co-viewing in these contexts. Our findings highlight how Screenr supported interrogation of the production qualities and claims of shows, promoted critical discourse around the motivations of programmes, and engaged participants in reflecting on their own assumptions and views. We situate our results within the context of existing second-screening co-viewing work, discuss implications for such technologies to support critical engagement with socio-political media, and provide design implications for future digital technologies in this domain.

The emergence of fake news, as well as filter bubbles and echo chambers, has precipitated renewed attention upon the ways in which news is consumed, shared and reflected and commented upon. While online news comments sections offer space for pluralist and critical discussion, studies suggest that this rarely occurs. Motivated by common practices of annotating, defacing and scribbling on physical newspapers, we built a mobile app -- Newsr -- that supports co-annotation, in the form of graffiti, on online news articles, which we evaluated in-the-wild for one month. We report on how the app encouraged participants to reflect upon the act of choosing news stories, whilst promoting exploration, the critique of content, and the exposure of bias within the writing. Our findings highlight how the re-design of interactive online news experiences can facilitate more directed, "in-the-moment" critique of online news stories as well as encourage readers to expand the range of news content they read.

The recent proliferation of a reality TV genre that focusses on welfare recipients has led to concerns that prime-time media experiences are exacerbating misconceptions, and stifling critical debate, around major societal issues such as welfare reform and poverty. Motivated by arguments that 'second screening' practices offer opportunities to engage viewers with issues of political concern, we describe the design and evaluation of two smartphone apps that facilitate and promote more critical live-viewing of reality TV. Our apps, Spotting Guide and Moral Compass, encourage users to identify, categorise, tag and filter patterns and tropes within reality TV, as well as reinterpret social media posts associated with their broadcast. We show that such interactions encourage critical thinking around typical editing and production techniques and foster co-discussion and reflection amongst viewers. We discuss, more broadly, how these interactions encourage users to identify the wider consequences and framings of reality TV, and offer implications and considerations for design that provokes criticality and reflection in second screening contexts.

Bots are estimated to account for well over half of all web traffic, yet they remain an understudied topic in HCI. In this paper we present the findings of an analysis of 2284 submissions across three discussion groups dedicated to the request, creation and discussion of bots on Reddit. We set out to examine the qualities and functionalities of bots and the practical and social challenges surrounding their creation and use. Our findings highlight the prevalence of misunderstandings around the capabilities of bots, misalignments in discourse between novices who request and more expert members who create them, and the prevalence of requests that are deemed to be inappropriate for the Reddit community. In discussing our findings, we suggest future directions for the design and development of tools that support more carefully guided and reflective approaches to bot development for novices, and tools to support exploring the consequences of contextually-inappropriate bot ideas.

In this paper we investigate how online counter-discourse is designed, deployed and orchestrated by activists to challenge dominant narratives around socio-political issues. We focus on activism related to the UK broadcast media’s negative portrayal of welfare benefit claimants; portrayals characterised as “poverty porn” by critics. Using critical discourse analysis, we explore two activist campaigns countering the TV programme Benefits Street . Through content analysis of social media, associated traditional media texts, and interviews with activists, our analysis highlights the way activists leverage the specific technological affordances of different social media and other online platforms in order to manage and configure counter-discourse activities. We reveal how activists use different platforms to carefully control and contest discursive spaces, and the ways in which they utilise both online and offline activities in combination with new and broadcast media to build an audience for their work. We discuss the challenges associated with measuring the success of counter-discourse, and how activists rely on combinations of social media analytics and anecdotal feedback in order to ascertain that their campaigns are successful. We also discuss the often hidden power-relationships in such campaigns, especially where there is ambiguity regarding the grassroots legitimacy of activism, and where effort is placed into controlling and owning the propagation of counter-discourse. We conclude by highlighting a number of areas for further work around the blurred distinctions between corporate advocacy, digilantism and grassroots activism.

This paper presents an empirical investigation of how people appropriated Twitter for socio-political talk in response to a television (TV) portrayal of people supported by state welfare and benefits. Our findings reveal how online discussion during, and in-between, TV broadcasts was characterised by distinctly different qualities, topics and user behaviours. These findings offer design opportunities for social media services to (i) support more balanced real-time commentaries of politically-charged media, (ii) actively promote discussion to continue after, and between, programming; and (iii) incorporate different motivations and attitudes towards socio-political concerns, as well as different practices of communicating those concerns. We contribute to the developing HCI literature on how social media intersects with political and civic engagement and specifically highlight the ways in which Twitter interacts with other forms of media as a site of everyday socio-political talk and debate.