The Impact of Sentiment-driven Feedback on Knowledge Reuse in Online Communities

Knowledge reuse is of increasing importance for organizations. Despite the extant research, we still do not adequately understand the ways peers are motivated to reuse knowledge with the help of wiki technologies. In this paper, we study the motivation for knowledge reuse in a prominent instance of online social production: Wikipedia. Studying knowledge reuse in Wikipedia is important since Wikipedia has been able to leverage the benefits of efficient knowledge reuse to produce knowledge goods of relatively high quality. Specifically, we explore: 1) how Wikipedia editors (any peer who contributes to developing articles in Wikipedia) communicate their feedback toward each other’s work in peer conversations and 2) to what extent sentiment-driven feedback impacts the level of knowledge reuse in Wikipedia. The results show that displaying sentiment-driven feedback positively influenced the level of knowledge reuse. Our study further shows a significant difference in the level of knowledge reuse between editors who shared mainly positive or mainly negative sentiments. Specifically, displaying mainly positive feedback corresponded to a superior level of knowledge reuse than displaying mainly negative feedback. We contribute to the extant literature of online social production communities in general and Wikipedia in particular by providing a first building block for research on peer feedback’s role in developing and sustaining wiki-based knowledge reuse. We discuss our findings’ implications for theory and practice

Damage Detection and Mitigation in Open Collaboration Applications

Collaborative functionality is changing the way information is amassed, refined, and disseminated in online environments. A subclass of these systems characterized by open collaboration uniquely allow participants to *modify* content with low barriers-to-entry. A prominent example and our case study, English Wikipedia, exemplifies the vulnerabilities: 7%+ of its edits are blatantly unconstructive. Our measurement studies show this damage manifests in novel socio-technical forms, limiting the effectiveness of computational detection strategies from related domains. In turn this has made much mitigation the responsibility of a poorly organized and ill-routed human workforce. We aim to improve all facets of this incident response workflow. Complementing language based solutions we first develop content agnostic predictors of damage. We implicitly glean reputations for system entities and overcome sparse behavioral histories with a spatial reputation model combining evidence from multiple granularity. We also identify simple yet indicative metadata features that capture participatory dynamics and content maturation. When brought to bear over damage corpora our contributions: (1) advance benchmarks over a broad set of security issues ( vandalism ), (2) perform well in the first anti-spam specific approach, and (3) demonstrate their portability over diverse open collaboration use cases. Probabilities generated by our classifiers can also intelligently route human assets using prioritization schemes optimized for capture rate or impact minimization. Organizational primitives are introduced that improve workforce efficiency. The whole of these strategies are then implemented into a tool ( STiki ) that has been used to revert 350,000+ damaging instances from Wikipedia. These uses are analyzed to learn about human aspects of the edit review process, properties including scalability, motivation, and latency. Finally, we conclude by measuring practical impacts of work, discussing how to better integrate our solutions, and revealing outstanding vulnerabilities that speak to research challenges for open collaboration security

Trust in Collaborative Web Applications

Collaborative functionality is increasingly prevalent in web applications. Such functionality permits individuals to add - and sometimes modify - web content, often with minimal barriers to entry. Ideally, large bodies of knowledge can be amassed and shared in this manner. However, such software also provide a medium for nefarious persons to operate. By determining the extent to which participating content/agents can be trusted, one can identify useful contributions. In this work, we define the notion of trust for Collaborative Web Applications and survey the state-of-the-art for calculating, interpreting, and presenting trust values. Though techniques can be applied broadly, Wikipedia\u27s archetypal nature makes it a focal point for discussion

Calculating and Presenting Trust in Collaborative Content

Collaborative functionality is increasingly prevalent in Internet applications. Such functionality permits individuals to add -- and sometimes modify -- web content, often with minimal barriers to entry. Ideally, large bodies of knowledge can be amassed and shared in this manner. However, such software also provides a medium for biased individuals, spammers, and nefarious persons to operate. By computing trust/reputation for participating agents and/or the content they generate, one can identify quality contributions. In this work, we survey the state-of-the-art for calculating trust in collaborative content. In particular, we examine four proposals from literature based on: (1) content persistence, (2) natural-language processing, (3) metadata properties, and (4) incoming link quantity. Though each technique can be applied broadly, Wikipedia provides a focal point for discussion. Finally, having critiqued how trust values are calculated, we analyze how the presentation of these values can benefit end-users and application security

Are anonymity-seekers just like everybody else? An analysis of contributions to Wikipedia from Tor

User-generated content sites routinely block contributions from users of privacy-enhancing proxies like Tor because of a perception that proxies are a source of vandalism, spam, and abuse. Although these blocks might be effective, collateral damage in the form of unrealized valuable contributions from anonymity seekers is invisible. One of the largest and most important user-generated content sites, Wikipedia, has attempted to block contributions from Tor users since as early as 2005. We demonstrate that these blocks have been imperfect and that thousands of attempts to edit on Wikipedia through Tor have been successful. We draw upon several data sources and analytical techniques to measure and describe the history of Tor editing on Wikipedia over time and to compare contributions from Tor users to those from other groups of Wikipedia users. Our analysis suggests that although Tor users who slip through Wikipedia's ban contribute content that is more likely to be reverted and to revert others, their contributions are otherwise similar in quality to those from other unregistered participants and to the initial contributions of registered users.Comment: To appear in the IEEE Symposium on Security & Privacy, May 202

Wikis for Teaching and Learning

An academic course presents an opportunity for all participants to collaborate for improving their knowledge. This collective improvement of knowledge is typically documented via material provided by the instructor and notes and assignments prepared by students. Over the course of a semester, these materials provide not only the collective knowledge in that course, but also provide a chronological history of how the knowledge base evolved. The focus of this study is wiki collaboration in teaching & learning contexts. A wiki is a medium in which a group of individuals can work together asynchronously on an idea and easily capture the essence in a reusable format. Technically, a wiki is a collection of hyperlinked Web pages that are assembled with wiki software. With wikis, the line between reader and contributor is intentionally blurred. Further, wiki use reflects the view of an instructor as one who facilitates information sharing among learners rather than simply transmitting knowledge from themselves to their students. Our initial motivation to explore the usefulness of wikis for teaching and learning was driven by the fact that wikis provide a medium in which several individuals could asynchronously work together on an idea and easily capture the essence in a reusable format. We found that: (1) Wikis can be can be used for a variety of tasks ranging from signup sheet for students to self organize, to undertaking business analyses, to analyzing policy positions; (2) Instructor support and facilitation is key; and (3) Ease-of-use issues are present but do not preclude success

The Use of Social Media in Enterprises for Communication, Collaboration, and Knowledge Management

Der Erfolg von Social Media im Internet hat dazu geführt, dass diese Technologie zunehmend auch in Unternehmen eingesetzt, oder über deren Implementierung nachgedacht wird. Durch die erwartete Verbesserung der Kommunikation und Interaktion zwischen Mitarbeitern auf der einen Seite und des Wissensmanagements auf der anderen Seite er-hoffen sich Entscheidungsträger in Unternehmen einen erheblichen betriebswirtschaftlichen Nutzen. Obwohl es einige Beispiele erfolgreicher Enterprise-Social-Media(ESM)-Implementierungen gibt und mehr als 90% der Fortune 500 Unternehmen ESM eingeführt haben oder dies planen, verfehlen 80% der ESM-Projekte die eingangs definierten Ziele. Während die Entscheidung, die Software einzukaufen, zentral getroffen wird, hängt deren Erfolg von der aktiven Partizipation der Mitarbeiter ab – wie sich anhand der genannten Statistiken zeigt, ist beides nicht zwangsläufig korreliert. Im Gegensatz zu organischem Wachstum, wie es in Social-Media-Anwendungen im Internet in den vergangenen Jahren beobachtet werden konnte (z.B. bei Facebook), ist die Nutzungsrate von internen ESM oft zu gering, um den Fortbestand der Community zu sichern. Es zeigt sich dabei verstärkt, dass passive Roll-Out-Strategien, die darauf vertrauen, dass es ein vergleichbares organisches Wachstum auch bei ESM gibt, zum Scheitern verurteilt sind. Viel-mehr müssen Analysen im Vorhinein das für einen spezifischen Anwendungsbereich geeignete Tool identifizieren, und Strategien entwickelt werden, wie Mitarbeiter für die Interaktion über die neuen Anwendungen gewonnen werden können. Da Ausgaben für Informationstechnologien bei einem geringen Nutzungsgrad nicht zu-rechtfertigen sind, trägt die vorliegende Dissertation in acht Essays dazu bei, verschiedene Facetten der ESM-Nutzung näher beleuchten und so zu einem besseren Verständnis des Themas und damit einhergehend einer effektiveren und effizienteren Implementierung von ESM beitragen. Sowohl die Analyse von Einflussfaktoren auf verschiedene Nutzungstypen von ESM, die Optimierung von Enterprise-Suchalgorithmen als auch die Neuinterpretation von Online-Produkt-Ratings können dabei helfen, die Veränderungen der internen und externen Kommunikation, Kollaboration und des Wissensmanagements, die sich durch den Einsatz von ESM ergeben, besser zu erklären und bedarfs-gerechter einzusetzen. Die theoretischen und praktischen Implikationen, welche sich konkret aus den einzelnen Essays ergeben, werden in den entsprechenden Abschnitten der jeweiligen Papiere erläutert

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

INCREASING THE WILLINGNESS TO COLLABORATE ONLINE: AN ANALYSIS OF SENTIMENT-DRIVEN INTERACTIONS IN PEER CONTENT PRODUCTION

We investigate mechanisms that trigger collaborative work behavior in online peer communities. We regard the collaboration among Wikipedia editors as a social process influenced by specific communication practices. We analyze and quantify the way Wikipedia editors communicate their feedback and support towards each others’ work in form of sentiments and opinions, and explore to what extent this influences online trust among them. We show that peer content production in Wikipedia is influenced by sharing sentiments during discussions among editors. At the global level, sharing sentiments positively influences the level of online trust. We also find a significant difference in the amount of online trust among editors who share mainly positive or mainly negative sentiments. We further suggest that providing and receiving especially supportive feedback expressed in form of positive sentiments and opinions may be beneficial in terms of virtual teamwork