• Skip to main content
  • Skip to primary sidebar
AAAI

AAAI

Association for the Advancement of Artificial Intelligence

    • AAAI

      AAAI

      Association for the Advancement of Artificial Intelligence

  • About AAAIAbout AAAI
    • AAAI Officers and Committees
    • AAAI Staff
    • Bylaws of AAAI
    • AAAI Awards
      • Fellows Program
      • Classic Paper Award
      • Dissertation Award
      • Distinguished Service Award
      • Allen Newell Award
      • Outstanding Paper Award
      • Award for Artificial Intelligence for the Benefit of Humanity
      • Feigenbaum Prize
      • Patrick Henry Winston Outstanding Educator Award
      • Engelmore Award
      • AAAI ISEF Awards
      • Senior Member Status
      • Conference Awards
    • AAAI Resources
    • AAAI Mailing Lists
    • Past AAAI Presidential Addresses
    • Presidential Panel on Long-Term AI Futures
    • Past AAAI Policy Reports
      • A Report to ARPA on Twenty-First Century Intelligent Systems
      • The Role of Intelligent Systems in the National Information Infrastructure
    • AAAI Logos
    • News
  • aaai-icon_ethics-diversity-line-yellowEthics & Diversity
  • Conference talk bubbleConferences & Symposia
    • AAAI Conference
    • AIES AAAI/ACM
    • AIIDE
    • IAAI
    • ICWSM
    • HCOMP
    • Spring Symposia
    • Summer Symposia
    • Fall Symposia
    • Code of Conduct for Conferences and Events
  • PublicationsPublications
    • AAAI Press
    • AI Magazine
    • Conference Proceedings
    • AAAI Publication Policies & Guidelines
    • Request to Reproduce Copyrighted Materials
  • aaai-icon_ai-magazine-line-yellowAI Magazine
    • Issues and Articles
    • Author Guidelines
    • Editorial Focus
  • MembershipMembership
    • Member Login
    • Developing Country List
    • AAAI Chapter Program

  • Career CenterCareer Center
  • aaai-icon_ai-topics-line-yellowAITopics
  • aaai-icon_contact-line-yellowContact

Home / Proceedings / Proceedings of the International AAAI Conference on Web and Social Media

A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms

February 1, 2023

Download PDF

Authors

Chase Geigle,Himel Dev,Hari Sundaram,ChengXiang Zhai

University of Illinois at Urbana-Champaign,University of Illinois at Urbana-Champaign,University of Illinois at Urbana-Champaign,University of Illinois at Urbana-Champaign


DOI:

10.1609/icwsm.v13i01.3220


Abstract:

This paper proposes a generative model for discovering user roles and community role compositions in Community Question Answering (CQA) platforms. While past research shows that participants play different roles in online communities, automatically discovering these roles and providing a summary of user behavior that is readily interpretable remains an important challenge. Furthermore, there has been relatively little insight into the distribution of these roles between communities. Does a community’s composition over user roles vary as a function of topic? How does it relate to the health of the underlying community? Does role composition evolve over time? The generative model proposed in this paper, the mixture of Dirichlet-multinomial mixtures (MDMM) behavior model can (1) automatically discover interpetable user roles (as probability distributions over atomic actions) directly from log data, and (2) uncover community-level role compositions to facilitate such cross-community studies.A comprehensive experiment on all 161 non-meta communities on the StackExchange CQA platform demonstrates that our model can be useful for a wide variety of behavioral studies, and we highlight three empirical insights. First, we show interesting distinctions in question-asking behavior on StackExchange (where two distinct types of askers can be identified) and answering behavior (where two distinct roles surrounding answers emerge). Second, we find statistically significant differences in behavior compositions across topical groups of communities on StackExchange, and that those groups that have statistically significant differences in health metrics also have statistically significant differences in behavior compositions, suggesting a relationship between behavior composition and health. Finally, we show that the MDMM behavior model can be used to demonstrate similar but distinct evolutionary patterns between topical groups.

Topics: ICWSM

Primary Sidebar

HOW TO CITE:

Chase Geigle,Himel Dev,Hari Sundaram,ChengXiang Zhai A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms Proceedings of the International AAAI Conference on Web and Social Media (2019) 181-192.

Chase Geigle,Himel Dev,Hari Sundaram,ChengXiang Zhai A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms ICWSM 2019, 181-192.

Chase Geigle,Himel Dev,Hari Sundaram,ChengXiang Zhai (2019). A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms. Proceedings of the International AAAI Conference on Web and Social Media, 181-192.

Chase Geigle,Himel Dev,Hari Sundaram,ChengXiang Zhai. A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms. Proceedings of the International AAAI Conference on Web and Social Media 2019 p.181-192.

Chase Geigle,Himel Dev,Hari Sundaram,ChengXiang Zhai. 2019. A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms. "Proceedings of the International AAAI Conference on Web and Social Media". 181-192.

Chase Geigle,Himel Dev,Hari Sundaram,ChengXiang Zhai. (2019) "A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms", Proceedings of the International AAAI Conference on Web and Social Media, p.181-192

Chase Geigle,Himel Dev,Hari Sundaram,ChengXiang Zhai, "A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms", ICWSM, p.181-192, 2019.

Chase Geigle,Himel Dev,Hari Sundaram,ChengXiang Zhai. "A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms". Proceedings of the International AAAI Conference on Web and Social Media, 2019, p.181-192.

Chase Geigle,Himel Dev,Hari Sundaram,ChengXiang Zhai. "A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms". Proceedings of the International AAAI Conference on Web and Social Media, (2019): 181-192.

Chase Geigle,Himel Dev,Hari Sundaram,ChengXiang Zhai. A Generative Model for Discovering Action-Based Roles and Community Role Compositions on Community Question Answering Platforms. ICWSM[Internet]. 2019[cited 2023]; 181-192.


ISSN: 2334-0770


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept All”, you consent to the use of ALL the cookies. However, you may visit "Cookie Settings" to provide a controlled consent.
Cookie SettingsAccept All
Manage consent

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary
Always Enabled
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
CookieDurationDescription
cookielawinfo-checkbox-analytics11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
cookielawinfo-checkbox-functional11 monthsThe cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
cookielawinfo-checkbox-others11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
cookielawinfo-checkbox-performance11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
viewed_cookie_policy11 monthsThe cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.
Functional
Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.
Performance
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Analytics
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
Advertisement
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.
Others
Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet.
SAVE & ACCEPT