Predicting the Quality of Short Narratives from Social Media

An important and difficult challenge in building computational models for narratives is the automatic evaluation of narrative quality. Quality evaluation connects narrative understanding and generation as generation systems need to evaluate their own products. To circumvent difficulties in acquiring annotations, we employ upvotes in social media as an approximate measure for story quality. We collected 54,484 answers from a crowd-powered question-and-answer website, Quora, and then used active learning to build a classifier that labeled 28,320 answers as stories. To predict the number of upvotes without the use of social network features, we create neural networks that model textual regions and the interdependence among regions, which serve as strong benchmarks for future research. To our best knowledge, this is the first large-scale study for automatic evaluation of narrative quality.Comment: 7 pages, 2 figures. Accepted at the 2017 IJCAI conferenc

How to Ask for a Favor: A Case Study on the Success of Altruistic Requests

Requests are at the core of many social media systems such as question & answer sites and online philanthropy communities. While the success of such requests is critical to the success of the community, the factors that lead community members to satisfy a request are largely unknown. Success of a request depends on factors like who is asking, how they are asking, when are they asking, and most critically what is being requested, ranging from small favors to substantial monetary donations. We present a case study of altruistic requests in an online community where all requests ask for the very same contribution and do not offer anything tangible in return, allowing us to disentangle what is requested from textual and social factors. Drawing from social psychology literature, we extract high-level social features from text that operationalize social relations between recipient and donor and demonstrate that these extracted relations are predictive of success. More specifically, we find that clearly communicating need through the narrative is essential and that that linguistic indications of gratitude, evidentiality, and generalized reciprocity, as well as high status of the asker further increase the likelihood of success. Building on this understanding, we develop a model that can predict the success of unseen requests, significantly improving over several baselines. We link these findings to research in psychology on helping behavior, providing a basis for further analysis of success in social media systems.Comment: To appear at ICWSM 2014. 10pp, 3 fig. Data and other info available at http://www.mpi-sws.org/~cristian/How_to_Ask_for_a_Favor.htm

MoralStrength: Exploiting a Moral Lexicon and Embedding Similarity for Moral Foundations Prediction

Moral rhetoric plays a fundamental role in how we perceive and interpret the information we receive, greatly influencing our decision-making process. Especially when it comes to controversial social and political issues, our opinions and attitudes are hardly ever based on evidence alone. The Moral Foundations Dictionary (MFD) was developed to operationalize moral values in the text. In this study, we present MoralStrength, a lexicon of approximately 1,000 lemmas, obtained as an extension of the Moral Foundations Dictionary, based on WordNet synsets. Moreover, for each lemma it provides with a crowdsourced numeric assessment of Moral Valence, indicating the strength with which a lemma is expressing the specific value. We evaluated the predictive potentials of this moral lexicon, defining three utilization approaches of increased complexity, ranging from lemmas' statistical properties to a deep learning approach of word embeddings based on semantic similarity. Logistic regression models trained on the features extracted from MoralStrength, significantly outperformed the current state-of-the-art, reaching an F1-score of 87.6% over the previous 62.4% (p-value<0.01), and an average F1-Score of 86.25% over six different datasets. Such findings pave the way for further research, allowing for an in-depth understanding of moral narratives in text for a wide range of social issues

Evaluating Engagement in Digital Narratives from Facial Data

Engagement researchers indicate that the engagement level of people in a narrative has an influence on people's subsequent story-related attitudes and beliefs, which helps psychologists understand people's social behaviours and personal experience. With the arrival of multimedia, the digital narrative combines multimedia features (e.g. varying images, music and voiceover) with traditional storytelling. Research on digital narratives has been widely used in helping students gain problem-solving and presentation skills as well as supporting child psychologists investigating children's social understanding such as family/peer relationships through completing their digital narratives. However, there is little study on the effect of multimedia features in digital narratives on the engagement level of people. This research focuses on measuring the levels of engagement of people in digital narratives and specifically on understanding the media effect of digital narratives on people's engagement levels. Measurement tools are developed and validated through analyses of facial data from different age groups (children and young adults) in watching stories with different media features of digital narratives. Data sources used in this research include a questionnaire with Smileyometer scale and the observation of each participant's facial behaviours

Domestic Violence in Men\u27s and Women\u27s Magazines: Women Are Guilty of Choosing the Wrong Men, Men Are Not Guilty of Hitting Women

Men\u27s and women\u27s magazine discourse on domestic violence characterizes women as guilty of choosing the wrong men but does not hold men responsible for hitting women. Using qualitative narrative analysis on 10 leading titles over 10 years, I find an ongoing tolerance for and celebration of domestic violence in men\u27s magazines and an enduring expectation in women\u27s that women bear responsibility for both genders. No magazines discuss patriarchal cultural structures that enable violence against women

Video games as meaningful entertainment experiences

We conducted an experiment to examine individuals’ perceptions of enjoyable and meaningful video games and the game characteristics and dimensions of need satisfaction associated with enjoyment and appreciation. Participants (N = 512) were randomly assigned to 1 of 2 groups that asked them to recall a game that they found either particularly fun or particularly meaningful, and to then rate their perceptions of the game that they recalled. Enjoyment was high for both groups, though appreciation was higher in the meaningful- than fun-game condition. Further, enjoyment was most strongly associated with gameplay characteristics and satisfaction of needs related to competency and autonomy, whereas appreciation was most strongly associated with story characteristics and satisfaction of needs related to insight and relatedness

Playing with the future: social irrealism and the politics of aesthetics

In this paper we wish to explore the political possibilities of video games. Numerous scholars now take seriously the place of popular culture in the remaking of our geographies, but video games still lag behind. For us, this tendency reflects a general response to them as imaginary spaces that are separate from everyday life and 'real' politics. It is this disconnect between abstraction and lived experience that we complicate by defining play as an event of what Brian Massumi calls lived abstraction. We wish to short-circuit the barriers that prevent the aesthetic resonating with the political and argue that through their enactment, video games can animate fantastical futures that require the player to make, and reflect upon, profound ethical decisions that can be antagonistic to prevailing political imaginations. We refer to this as social irrealism to demonstrate that reality can be understood through the impossible and the imagined