Nowadays, public debates often take place on social media platforms like Facebook or Twitter and can be characterized as asynchronous, protracted and ill-structured. The Massive Open Online Deliberation (MOOD) platform aims to structure these debates. Essential is that the platform can differentiate between the moral acceptability and the social acceptance of a debate outcome. We briefly descri...

Despite the impact that Internet-mediated advocacy organizations have had on American politics over the last decade, we are still learning about how they work. This is even truer for Internet-mediated issue specialists that focus on a single issue, such as climate change. Based on interviews with key staff members of two climate change advocacy campaigns, this article examines how these organiz...

BACKGROUND The ethical discussion about abortion has been polarized in Finland and the Republic of Ireland, two European countries with very different abortion legislation (liberal vs. highly restrictive). The aim of the present study was to analyze experiential thinking patterns and argumentative strategies in political and layperson debates regarding induced abortion. METHODS The content of...

We propose a method for the task of identifying the general positions of users in online debates, i.e., support or oppose the main topic of an online debate, by exploiting local information in their remarks within the debate. An online debate is a forum where each user post an opinion on a particular topic while other users state their positions by posting their remarks within the debate. The s...

News consumption is moving online. If this move fundamentally changes how news is produced and consumed it will have important ramifications for politics. In this chapter we formulate a model of the supply and demand of news online that is motivated by descriptive features of online news consumption. We estimate the demand model using a combination of microdata and aggregate moments from a pane...

Online debate forums present a valuable opportunity for the understanding and modeling of dialogue. To understand these debates, a key challenge is inferring the stances of the participants, all of which are interrelated and dependent. While collectively modeling users’ stances has been shown to be effective (Walker et al., 2012c; Hasan and Ng, 2013), there are many modeling decisions whose ram...

We study the problem of agreement and disagreement detection in online discussions. An isotonic Conditional Random Fields (isotonic CRF) based sequential model is proposed to make predictions on sentenceor segment-level. We automatically construct a socially-tuned lexicon that is bootstrapped from existing general-purpose sentiment lexicons to further improve the performance. We evaluate our ag...