SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment

Because word semantics can substantially change across communities and contexts, capturing domain-specific word semantics is an important challenge. Here, we propose SEMAXIS, a simple yet powerful framework to characterize word semantics using many semantic axes in word- vector spaces beyond sentiment. We demonstrate that SEMAXIS can capture nuanced semantic representations in multiple online communities. We also show that, when the sentiment axis is examined, SEMAXIS outperforms the state-of-the-art approaches in building domain-specific sentiment lexicons.Comment: Accepted in ACL 2018 as a full pape

Loyalty in Online Communities

Loyalty is an essential component of multi-community engagement. When users have the choice to engage with a variety of different communities, they often become loyal to just one, focusing on that community at the expense of others. However, it is unclear how loyalty is manifested in user behavior, or whether loyalty is encouraged by certain community characteristics. In this paper we operationalize loyalty as a user-community relation: users loyal to a community consistently prefer it over all others; loyal communities retain their loyal users over time. By exploring this relation using a large dataset of discussion communities from Reddit, we reveal that loyalty is manifested in remarkably consistent behaviors across a wide spectrum of communities. Loyal users employ language that signals collective identity and engage with more esoteric, less popular content, indicating they may play a curational role in surfacing new material. Loyal communities have denser user-user interaction networks and lower rates of triadic closure, suggesting that community-level loyalty is associated with more cohesive interactions and less fragmentation into subgroups. We exploit these general patterns to predict future rates of loyalty. Our results show that a user's propensity to become loyal is apparent from their first interactions with a community, suggesting that some users are intrinsically loyal from the very beginning.Comment: Extended version of a paper appearing in the Proceedings of ICWSM 2017 (with the same title); please cite the official ICWSM versio

Exploring the user engagement factors in computer mediated communication

User engagement can be defined as the perception of the user to qualify the experience towards certain application, which focus on the positive aspects of the interaction through Internet in the context of the desire to use it continuously and for longer time. It is fundamental concept in the design of online applications regardless of the platform, driven by the observation that successful applications are not only used but those that work. However, user engagement in the technology advancement is a paradox phenomenon, as they recognize the potentiality but reluctant to adopt or they realize its use to solve problem but prefer the other solution for longer of time. The usual ways to evaluate them can be through self-report measures, observational methods, speech analysis or web analytics. These methods represent different compensations in term of configuration, the size of object and the scale of data to be collected. For example, some study might find detail and deep analysis but they are limited in term of generalizability, while the other might found out resourceful but denies the user reasoning and the context. During this millennial, the diffusion of innovation became the acceptable theory that majority academician and practical expert use to explain the phenomenon of the reason and factor to adopt certain product. Therefore, due to the assumption of several factors such as technology advancement and paradigm shift, this study want to explore current situation in the user engagement factors, which focused to computer mediated communication

Reputation Through Observation: Active Lurkers in an Online Community

Lurkers are the invisibile majority in a typical online community: Users that silently observe, consume, and become accustomed to a community without interacting actively. At some point in time, a small fraction of lurkers decides to start taking part in a community in some way. In this paper, we investigate the implications of lurking for the interactions of such newly-active users or active lurkers. In our analysis, we focus on a sub-community of the well- known Online Social Network (OSN) Reddit and track linguistic development of users’ comments as well as the development of user’s reputation. We analyze and compare the complete lifecycles of two types of users – active lurkers and non-lurkers. Our work gives new insights into the effects of lurking with respect to linguistic adaption of community habits and to reputation active lurkers are able to gain. In general, most influential and innovative contributions were submitted by former lurkers

Tracing Community Genealogy: How New Communities Emerge from the Old

The process by which new communities emerge is a central research issue in the social sciences. While a growing body of research analyzes the formation of a single community by examining social networks between individuals, we introduce a novel community-centered perspective. We highlight the fact that the context in which a new community emerges contains numerous existing communities. We reveal the emerging process of communities by tracing their early members' previous community memberships. Our testbed is Reddit, a website that consists of tens of thousands of user-created communities. We analyze a dataset that spans over a decade and includes the posting history of users on Reddit from its inception to April 2017. We first propose a computational framework for building genealogy graphs between communities. We present the first large-scale characterization of such genealogy graphs. Surprisingly, basic graph properties, such as the number of parents and max parent weight, converge quickly despite the fact that the number of communities increases rapidly over time. Furthermore, we investigate the connection between a community's origin and its future growth. Our results show that strong parent connections are associated with future community growth, confirming the importance of existing community structures in which a new community emerges. Finally, we turn to the individual level and examine the characteristics of early members. We find that a diverse portfolio across existing communities is the most important predictor for becoming an early member in a new community.Comment: 10 pages, 7 figures, to appear in Proceedings of ICWSM 2018, data and more at https://chenhaot.com/papers/community-genealogy.htm

Trajectories of Blocked Community Members: Redemption, Recidivism and Departure

Community norm violations can impair constructive communication and collaboration online. As a defense mechanism, community moderators often address such transgressions by temporarily blocking the perpetrator. Such actions, however, come with the cost of potentially alienating community members. Given this tradeoff, it is essential to understand to what extent, and in which situations, this common moderation practice is effective in reinforcing community rules. In this work, we introduce a computational framework for studying the future behavior of blocked users on Wikipedia. After their block expires, they can take several distinct paths: they can reform and adhere to the rules, but they can also recidivate, or straight-out abandon the community. We reveal that these trajectories are tied to factors rooted both in the characteristics of the blocked individual and in whether they perceived the block to be fair and justified. Based on these insights, we formulate a series of prediction tasks aiming to determine which of these paths a user is likely to take after being blocked for their first offense, and demonstrate the feasibility of these new tasks. Overall, this work builds towards a more nuanced approach to moderation by highlighting the tradeoffs that are in play.Comment: To appear in Proceedings of the 2019 World Wide Web Conference (WWW '19), May 13-17, 2019, San Francisco, CA, USA. Code and data available as part of ConvoKit: convokit.cornell.ed

Arrels del trumpisme : Homofilia i rebuda social en el suport a Donald Trump a Reddit

Estudiem l’emergència del suport a Donald Trump a la discussió política de Reddit. Amb gairebé 800k subscriptors, “r/The_Donald” és una de les comunitats més grans de Reddit i un dels nuclis principals de partidaris de Trump. Es va crear el 2015, poc després que Donald Trump comencés la campanya presidencial. Utilitzant només dades del 2012, prediem la versemblança de ser un partidari de Donald Trump el 2016, l’any de les darreres eleccions presidencials dels EUA. Per caracteritzar el comportament dels simpatitzants de Trump, partim de tres hipòtesis sociològiques diferents: l’homofília, la influència social i la rebuda social. Operacionalitzem cada hipòtesi com un conjunt de característiques per cada usuari i entrenem classificadors per predir-ne la participació en r/The_Donald. Trobem que les característiques basades en l’homofília i la rebuda social són els senyals més predictius. Per contra, no observem un fort impacte dels mecanismes d’influència social. També realitzem una introspecció del model amb més bons resultats per construir una “persona” del típic partidari de Donald Trump a Reddit. Trobem evidències que els trets més prominents inclouen una predominança d’interessos masculins, una inclinació política conservadora i llibertariana i vincles amb contingut políticament incorrecte i conspiratori.Estudiamos la emergencia del soporte a Donald Trump en la discusión política de Reddit. Con casi 800k suscriptores, “r/The_Donald” es una de las comunidades más grandes de Reddit y uno de los núcleos principales de partidarios de Trump. Se creó el 2015, poco después que Donald Trump comenzara la campaña electoral. Utilizando solamente datos del 2012, predecimos la verosimilitud de ser un partidario de Donald Trump el 2016, el año de las últimas elecciones presidenciales de los EEUU. Para caracterizar el comportamiento de los simpatizantes de Trump, partimos de tres hipótesis sociológicas diferentes: la homofilia, la influencia social y el recibimiento social. Operacionalizamos cada hipótesis como un conjunto de características por cada usuario y entrenamos clasificadores para predecir la participación la participación en r/The_Donald. Encontramos que las características basadas en la homofilia y el recibimiento social son los señales más predictivos. En cambio, no observamos un fuerte impacto de los mecanismos de influencia social. También realizamos una introspección del modelo con mejores resultados para construir una “persona” del típico partidario de Donald Trump en Reddit. Encontramos evidencias que los rasgos más prominentes incluyen una predominancia de intereses masculinos, una inclinación política conservadora y libertaria y vínculos con contenido políticamente incorrecto y conspiratorio.We study the emergence of support for Donald Trump in Reddit’s political discussion. With almost 800k subscribers, “r/The Donald” is one of the largest communities on Reddit, and one of the main hubs for Trump supporters. It was created in 2015, shortly after Donald Trump began his presidential campaign. By using only data from 2012, we predict the likelihood of being a supporter of Donald Trump in 2016, the year of the last US presidential elections. To characterize the behavior of Trump supporters, we draw from three different sociological hypotheses: homophily, social influence, and social feedback. We operationalize each hypothesis as a set of features for each user, and train classifiers to predict their participation in r/The Donald. We find that homophily-based and social feedback-based features are the most predictive signals. Conversely, we do not observe a strong impact of social influence mechanisms. We also perform an introspection of the best-performing model to build a “persona” of the typical supporter of Donald Trump on Reddit. We find evidence that the most prominent traits include a predominance of masculine interests, a conservative and libertarian political leaning, and links with politically incorrect and conspiratorial content.Outgoin

The Haptiverse: A Platform for Reuse of Haptic Content

Research into haptic technology has accelerated over the past decade, producing more devices and content than ever before. However, due to the innate diversity of its hardware and the sense of touch itself, existing haptic experiences are limited to a specific physical technology or interaction modality. To remedy this, we introduce the Haptiverse, a platform for reuse of heterogeneous haptic content. The collection will be designed to internally motivate hapticians, who are designers, researchers, or developers of haptic experiences, to share their work with the global haptics community. We implement design features to target each basic psychological need in order for users to feel internally motivated to continue to share their work using the collection. Our results show that there was a positive influence in users’ perceived competence when interacting with a multi-step form to upload content. Users’ perceived relatedness and autonomy were also positively influenced after reading the Haptiverse’s mission statement. In addition, novice hapticians reported higher levels of perceived relatedness after reading a mission statement that incorporated both autonomy and relatedness intrinsic goals. We present a minimum viable product of the Haptiverse and design recommendations to further support hapticians when sharing haptic content