925 research outputs found
Semantic Sentiment Analysis of Twitter Data
Internet and the proliferation of smart mobile devices have changed the way
information is created, shared, and spreads, e.g., microblogs such as Twitter,
weblogs such as LiveJournal, social networks such as Facebook, and instant
messengers such as Skype and WhatsApp are now commonly used to share thoughts
and opinions about anything in the surrounding world. This has resulted in the
proliferation of social media content, thus creating new opportunities to study
public opinion at a scale that was never possible before. Naturally, this
abundance of data has quickly attracted business and research interest from
various fields including marketing, political science, and social studies,
among many others, which are interested in questions like these: Do people like
the new Apple Watch? Do Americans support ObamaCare? How do Scottish feel about
the Brexit? Answering these questions requires studying the sentiment of
opinions people express in social media, which has given rise to the fast
growth of the field of sentiment analysis in social media, with Twitter being
especially popular for research due to its scale, representativeness, variety
of topics discussed, as well as ease of public access to its messages. Here we
present an overview of work on sentiment analysis on Twitter.Comment: Microblog sentiment analysis; Twitter opinion mining; In the
Encyclopedia on Social Network Analysis and Mining (ESNAM), Second edition.
201
An Army of Me: Sockpuppets in Online Discussion Communities
In online discussion communities, users can interact and share information
and opinions on a wide variety of topics. However, some users may create
multiple identities, or sockpuppets, and engage in undesired behavior by
deceiving others or manipulating discussions. In this work, we study
sockpuppetry across nine discussion communities, and show that sockpuppets
differ from ordinary users in terms of their posting behavior, linguistic
traits, as well as social network structure. Sockpuppets tend to start fewer
discussions, write shorter posts, use more personal pronouns such as "I", and
have more clustered ego-networks. Further, pairs of sockpuppets controlled by
the same individual are more likely to interact on the same discussion at the
same time than pairs of ordinary users. Our analysis suggests a taxonomy of
deceptive behavior in discussion communities. Pairs of sockpuppets can vary in
their deceptiveness, i.e., whether they pretend to be different users, or their
supportiveness, i.e., if they support arguments of other sockpuppets controlled
by the same user. We apply these findings to a series of prediction tasks,
notably, to identify whether a pair of accounts belongs to the same underlying
user or not. Altogether, this work presents a data-driven view of deception in
online discussion communities and paves the way towards the automatic detection
of sockpuppets.Comment: 26th International World Wide Web conference 2017 (WWW 2017
Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions
In online communities, antisocial behavior such as trolling disrupts
constructive discussion. While prior work suggests that trolling behavior is
confined to a vocal and antisocial minority, we demonstrate that ordinary
people can engage in such behavior as well. We propose two primary trigger
mechanisms: the individual's mood, and the surrounding context of a discussion
(e.g., exposure to prior trolling behavior). Through an experiment simulating
an online discussion, we find that both negative mood and seeing troll posts by
others significantly increases the probability of a user trolling, and together
double this probability. To support and extend these results, we study how
these same mechanisms play out in the wild via a data-driven, longitudinal
analysis of a large online news discussion community. This analysis reveals
temporal mood effects, and explores long range patterns of repeated exposure to
trolling. A predictive model of trolling behavior shows that mood and
discussion context together can explain trolling behavior better than an
individual's history of trolling. These results combine to suggest that
ordinary people can, under the right circumstances, behave like trolls.Comment: Best Paper Award at CSCW 201
Analyzing collaborative learning processes automatically
In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in
Longitudinal associations between keeping a secret and psychosocial adjustment in adolescence
Increasing bodies of evidence suggest that keeping secrets may be detrimental to well-being and adjustment, whereas confiding secrets may alleviate the detriments of secrecy and benefit well-being and adjustment. However, few studies have addressed the consequences of keeping and confiding secrets simultaneously, and even fewer have done so longitudinally. This article reports on a two-wave longitudinal survey study among 278 adolescents (aged 13-18 years) that examined the associations of keeping and confiding a specific secret with psychosocial adjustment. Results confirmed a hypothesized longitudinal contribution of keeping a secret all to oneself to psychosocial problems, including depressive mood, low self-concept clarity, low self-control, loneliness, and poor relationship quality. Furthermore, confiding versus continuing to keep a secret all to oneself was associated with decreased psychosocial problems after six months, whereas starting to keep a secret versus not doing so was associated with increased psychosocial problems. These results suggest that the keeping or confiding of secrets may affect adolescents' psychosocial well-being and adjustment. © 2008 The International Society for the Study of Behavioural Development
Expression of Emotion: When It Causes Trauma and When It Helps
The idea that clients should be encouraged to express strong emotion regarding the traumas they have suffered is widely assumed. This paper asks whether the empirical literature supports the underlying assumption that emotional expression leads to positive outcomes (better health and dissipation of distress). Studies in which individuals who have been given an opportunity to express emotions about past traumas are compared with subjects placed in appropriate control conditions are reviewed. The empirical literature suggests that eliciting emotion is harmful when it is not associated with reappraisal of past trauma, but helpful when the reappraisal occurs. The following guideline emerges: if trauma is to be revisited, it should be accompanied by reappraisal. Since this is sometimes difficult to engineer, alternative approaches for working with victims of trauma, not involving revisiting the trauma, are offered. Additionally, it is suggested that it can be helpful to identify the nature of the problem arising from the traumatic experience, and then provide therapeutic intervention that addresses the problem
More than words: The influence of affective content and linguistic style matches in online reviews on conversion rates
Customers increasingly rely on other consumers' reviews to make purchase decisions online. New insights into the customer review phenomenon can be derived from studying the semantic content and style properties of verbatim customer reviews to examine their influence on online retail sites' conversion rates. The authors employ text mining to extract changes in affective content and linguistic style properties of customer book reviews on Amazon.com. A dynamic panel data model reveals that the influence of positive affective content on conversion rates is asymmetrical, such that greater increases in positive affective content in customer reviews have a smaller effect on subsequent increases in conversion rate. No such tapering-off effect occurs for changes in negative affective content in reviews. Furthermore, positive changes in affective cues and increasing congruence with the product interest group's typical linguistic style directly and conjointly increase conversion rates. These findings suggest that managers should identify and promote the most influential reviews in a given product category, provide instructions to stimulate reviewers to write powerful reviews, and adapt the style of their own editorial reviews to the relevant product category
A Decade of Shared Tasks in Digital Text Forensics at PAN
[EN] Digital text forensics aims at examining the originality and
credibility of information in electronic documents and, in this regard, to extract and analyze information about the authors of these documents. The research field has been substantially developed during the last decade. PAN is a series of shared tasks that started in 2009 and significantly contributed to attract the attention of the research community in well-defined digital text forensics tasks. Several benchmark datasets have been developed to assess the state-of-the-art performance in a wide range of tasks. In this paper, we present the evolution of both the examined tasks and the developed datasets during the last decade. We also briefly introduce the upcoming PAN 2019 shared tasks.We are indebted to many colleagues and friends who contributed greatly to PAN's tasks: Maik Anderka, Shlomo Argamon, Alberto Barrón-Cedeño, Fabio Celli, Fabio Crestani, Walter Daelemans, Andreas Eiselt, Tim Gollub,
Parth Gupta, Matthias Hagen, Teresa Holfeld, Patrick Juola, Giacomo Inches, Mike
Kestemont, Moshe Koppel, Manuel Montes-y-Gómez, Aurelio Lopez-Lopez, Francisco
Rangel, Miguel Angel Sánchez-Pérez, Günther Specht, Michael Tschuggnall, and Ben
Verhoeven. Our special thanks go to PAN¿s sponsors throughout the years and not
least to the hundreds of participants.Potthast, M.; Rosso, P.; Stamatatos, E.; Stein, B. (2019). A Decade of Shared Tasks in Digital Text Forensics at PAN. Lecture Notes in Computer Science. 11438:291-300. https://doi.org/10.1007/978-3-030-15719-7_39S2913001143
Trait and state authenticity across cultures
We examined the role of culture in both trait and state authenticity, asking whether the search for and experience of the 'true self' is a uniquely Western phenomenon or is relevant cross-culturally. We tested participants from the US, China, India, and Singapore. US participants reported higher average levels of trait authenticity than those from Eastern cultures (i.e., China, India, Singapore), but this effect was partially explained by cultural differences in self-construal and thinking style. Importantly, the experience of state authenticity, and especially state inauthenticity, was more similar than different across cultures. In all, people from different cultures do experience authenticity, even if they do not endorse the (Western) value of “independence.” The findings contribute to a more nuanced understanding of state authenticity
- …