ICA 2019 Computational Methods Programme

Please find below an overview of Computational Methods sessions for ICA 2019. Thanks to all submitters and reviewers for the fantastic lineup. We’re looking forward to meeting you all again in Washington! See the full ICA programme here.

Computational approaches to political communication

(25-May-2019 11:00 AM-12:15 PM, Morgan (Washington Hilton, Lobby Level))

  • The Dynamic Relationship between News Frames and Real-World Events: A Hidden Markov Model Approach(F. R. Hopp; J. T. Fisher; R. Weber)
  • Do People Create Filter Bubbles?: A Computational Examination of Political Network Curation on Twitter(J. Yang)
  • Sticks in a Bundle are Unbreakable? The Effect of Polarization on Parties’ Compromise Rhetoric in 7 European Democracies, 1995 – 2013(M. van der Velden; A. Alberto)
  • Does Partisan News Polarize America?:
    A Field Experiment on the Effects of Forced Partisan Media Exposure
    (P. Barberá; J. Yang; A. Guess; S. Munzert)
  • Search Media and Elections: Investigating Partisanship in Political Search Results(D. Metaxa-Kakavouli; J. S. Park; J. A. Landay; J. Hancock)
  • Normalizing Swearing Online: An Unintended Consequence of a Large-Scale Political Movement in Hong Kong(H. Liang; G. Tang; F. Lee)

Applying computer vision in communication research

(25-May-2019 2:00 PM-3:15 PM, Morgan (Washington Hilton, Lobby Level))

  • Mechanisms of Collective Action: Measuring the Role of Violence, Identity, and Free-riding Using Geolocated Images(J. Joo; Z. Steinert-Threlkeld; D. Won)
  • Combining Machine Vision and Text Mining on Websites: Toward an Approach for Automated Multimodal Content Analysis(I. Lock; T. Araujo)
  • Is the Picture in Focus? Images in Social Movement Mobilization(A. Casas; N. Webb Williams; K. M. Aslett; J. D. Wilkerson)
  • The Use of Computer Vision to Analyze Visual Brand-related User Generated Content: A Comparison of YOLOV2, Google Cloud Vision, and Clarifai(A. Nanne; M. L. Antheunis; G. Noort; S. Wubben; E. Postma)
  • The Face of News in America: Applying Machine Vision to News Images(O. Lam; S. J. Wojcik; B. Broderick; A. G. Hughes)
  • How People Use Pictures in Political Protests and Why It Matters(H. Zhang; Y. Peng)

Network dynamics on social media

(25-May-2019 3:30 PM-4:45 PM, Oaklawn (Washington Hilton, Lobby Level))

  • Niche News and Peripheral Fragmentation: A Network Percolation Approach to the Analysis of News Consumption(T. Yang; S. Majo-Vazquez; S. Mukerjee; S. Gonzalez-Bailon)
  • Dynamics and Structure of Research Coverage across Online Media(I. Zakhlebin; A. Horvat)
  • Revisiting Ideological Segregation on the Web: A Block Model Approach to Audience Network Data(A. Y. Zhou; S. Gonzalez-Bailon)
  • Core-Periphery Decomposition of Networked Publics and Counterpublics(R. J. Gallagher; B. Foucault Welles)
  • Predicting Reposting Latency of News Content in Social Media: A Focus on Issue Attention, Temporal Usage Pattern, and Information Redundancy(L. Guan; H. Liang; J. Zhu)

Inductive and deductive methods for text analysis

(26-May-2019 8:00 AM-9:15 AM, Van Ness (Washington Hilton, First Floor))

  • When Does Garbage Stink? Imperfect Gold Standards and the Validation of Automated Content Analysis(H. Song; P. Tolochko; J. Eberl; F. Lind; T. Heidenreich; O. Eisele; E. Greussing; H. G. Boomgaarden)
  • Identification of Nationalist and Populist Emotions in Social Media: Based a New Massive Text Annotation Approach for Deep Learning(A. CHEN; Y. Hu; Q. Wu)
  • Exploring Topics Associations in Political News(Y. Fogel-Dror; S. Shenhav; T. Sheafer)
  • Mediated Morality on Twitter: Applying Distributed Dictionary Representation(Y. Chen; s. sun)
  • Computational methods for inductively extracting media frames: a comparative analysis(T. Nicholls)

Combating misinformation

(26-May-2019 9:30 AM-10:45 AM, Columbia 6 (Washington Hilton, Terrace Level))

  • The Electoral Dimension of Disinformation: Political Astroturfing on Twitter(J. Yang; F. Keller; D. Schoch; S. Stier)
  • Misinformation, Modularity, and Bot Zealots in the Wisdom of the Crowds(E. M. Forbush; D. R. Guilbeault; J. Gursky; D. Centola)
  • An Exploration of Fact-checking in Political Discussions on Reddit(D. Margolin; D. Parekh; D. Ruths)
  • Do I sound American? Predicting Disinformation Sharing of Russian IRA tweets from a Linguistic Perspective(J. Suk; J. Lukito; M. Su; S. Kim; C. Tong; Z. Sun; P. Sarma)
  • Crowdsourcing and Computer-assisted Analysis in Fact-checking: Insights from A Reddit Community(M. Yousuf; N. Hassan; M. Haque; J. Rivas; M. Islam)
  • Social media data as a window on disinformation campaign strategies(D. J. Ruck; A. Bentley; N. M. Rice; S. Allard; O. Manaev; C. Luther)
  • Buzzword “Fake News“ – Analyzing how commenters of a leading news forum use the term fake news via automated content analysis(S. Boberg; T. Schatto-Eckrodt; F. Wintterlin; T. Quandt)

Reflections on computational communication research

(26-May-2019 11:00 AM-12:15 PM, International Ballroom – East (Washington Hilton, Concourse Level))

  • The Temporal Turn in Communication Research:
    Time-Series Analyses Using Computational Approaches
    (C. Wells; D. V. Shah; J. C. Pevehouse; J. M. Foley; A. Pelled; J. Yang)
  • Towards a Stronger Theoretical Grounding of Computational Communication Science: A Review of Tried and Tested Social Theories(A. Waldherr; S. Geise; M. Mahrt; C. Katzenbach; C. Nuernbergk)
  • Discovering research topics in the communication field from 1997-2017 using structural topic modeling (STM)(C. Lim; M. Park; Y. Baek)
  • Pathways to access and acquire large data sets in communication science(S. Bruns; D. Possler; J. Niemann-Lenz)
  • Understanding Supply and Demand in Communication Research: A Computational Approach(C. Grill; C. Chan)
  • Geographical Location of Institutional Affiliation and Publication Types of Editors and Editorial Board Members in the Field of Communication(S. Youk; H. Park; J. Ryu; J. Lim; J. Han)

Beyond text analysis: Combining text, network, and image analysis techniques

(27-May-2019 8:00 AM-9:15 AM, International Ballroom – Center (Washington Hilton, Concourse Level))

  • From word vectors to cluster networks – an analysis of semantic fields in social media discussions using Word2vec, clustering and network analysis(S. Laaksonen; J. Pääkkönen; M. Jauho; V. Isotalo; M. Nelimarkka)
  • Automated Coding of Televised Leader Displays:
    A Computational Approach to Nonverbal Communication Research
    (J. Joo)
  • Blurring the Boundaries between Content Analysis and Reception Studies: Towards a Typology of Journalistic Articles’ Lifespans on Twitter(D. Compagno; B. Conan-Guez)
  • CASM: A Deep-Learning Approach for Identifying Collective Action Events with Text and Image Data from Social Media(J. Pan; H. Zhang)
  • Can You Hear the Echo? – Combining Sentiment and Social Network Analyses to Measure Opinion-Based Homogeneity in Social Media(D. Röchert; G. Neubaum; B. Ross; F. Brachten; S. Stieglitz)

Computational approaches to health communication

(27-May-2019 9:30 AM-10:45 AM, Holmead (Washington Hilton, Lobby Level))

  • Extended Abstract: First step towards an automated personalized persuasive conversational system: Investigating moderating effects of psychological factors(J. Zhang; Y. Oh; X. Wang; R. Kim; S. Yang; Z. Yu)
  • Detecting Intentional Self-Harm on Instagram: Development, Test, and Validation of an Automatic Image Recognition Algorithm to Discover Cutting-Related Posts(S. Scherr; F. Arendt; T. Frissen; J. M. Oramas)
  • More Connected but not More Productive: Analyzing Support for Interpersonal Communication in Wikis(N. E. TeBlunthuis; S. Narayan; W. Hale; B. Hill; A. Shaw)
  • Predicting health behavior change through automated content analysis of a peer-to-peer online forum: Application of supervised machine learning to substance use disorder recovery(R. F. Kornfield; y. liu; M. Chih; P. Sarma; D. V. Shah)
  • Identifying the social role of superusers in an online health social news community: A network analysis of r/health(W. Li; W. Wang; R. Bond)

Computational Methods Tool Demonstration

(27-May-2019 11:00 AM-12:15 PM, Kalorama (Washington Hilton, Lobby Level))

  • Increasing the Transparency of Big Text Data Collection in Computational Communication Science: Tools and Best Practices(E. Rinke; T. Dobbrick)
  • Measuring News Exposure using Surveys and Digital Trace Data: Exploring new connections and divergences(E. Menchen-Trevino; M. Wojcieszak; J. F. Gonçalves; B. Weeks)
  • Extracting semantic relations using syntax: an R package for
    querying and reshaping dependency trees.
    (K. Welbers; W. van Atteveldt; J. Kleinnijenhuis)
  • Agent-based testing: An automated approach toward artificial reactions to human behavior(M. Haim)
  • A Character Recognition Tool for Automated Content Analysis: A Facial Recognition Approach to Visual Content(J. Baldwin; R. Schmaelzle)
  • Tool demo: RISJbot – a web crawler for collecting structured news article content at scale(T. Nicholls)
  • Going beyond the wizard: Using computational methods for conversational agent communication research(T. Araujo)
  • 3bij3 – A framework for testing effects of recommender systems on news exposure(F. Loecherbach; D. Trilling)

Computational Methods Interactive Poster Session

(27-May-2019 12:30 PM-1:45 PM, International Terrace (Interactive Posters) (Washington Hilton, Terrace Level))

  • What Words Are Worth: National Science Foundation Grant Abstracts Indicate Award Funding(D. M. Markowitz)
  • Marketing Virtual Reality Games with Text: A Text Mining Analysis of Game Descriptions on Steam(J. C. Ho; X. Zhang)
  • Harnessing Collective Intelligence to Improve Decision-Making: Predicting Long-Term Success in P2P Lending(H. K. Dambanemuya; A. Horvat)
  • Understanding Public Opinion in Different Disaster Stages: A Case Study of Hurricane Irma(Z. Xu; K. Lachlan; L. Ellis; A. M. Rainear)
  • Ethnography of/in/through digital platforms: opportunities and challenges(A. Lusoli; F. Lesage)
  • Putting Your Best Pet Forward: Writing Style Predicts Duration of Pet Adoption(D. M. Markowitz)

Computational approaches to mobile communication

(28-May-2019 8:00 AM-9:15 AM, Columbia 9 (Washington Hilton, Terrace Level))

  • Balancing the Facts: The Sequencing of Thinking and Feeling on Mobile Phone Screens(N. Ram; M. Cho; B. Reeves; X. Yang)
  • Time Pattern of Mobile News Consumption(Y. LIU)
  • How do people use their smartphone? A data scientific approach to describe and identify user-related, system-related and context-related patterns in use(A. Hendrickson; L. De Marez; M. Martens; G. Muller; K. Ponnet; C. Schweitzer; M. M. Vanden Abeele)
  • Sequence Analysis of Media Use Data: Finding Patterns in Repetitive and Burst-like sequences(M. Wettstein)
  • Gathering Mobile News Consumption Traces: An Overview of Possibilities and a Prototype Tool based on Google Takeout(W. van Atteveldt; L. Bogaardt; V. van Hees; F. Loecherbach; J. Moeller; D. Trilling; K. Welbers)

Simulation studies of communication

(28-May-2019 9:30 AM-10:45 AM, Kalorama (Washington Hilton, Lobby Level))

  • An Evolutionary Model of the Emergence of Meanings(P. Oh; S. Kim)
  • The Network Dynamics of Conventions(J. A. Becker)
  • From the body, to the mind, to the public: An agent-based model of media effects on public opinion dynamics(H. Yan; J. Shanahan; A. Lang)
  • Networking Strategies at the Trade-off Between Individual and System-level Efficiency(K. Tanaka; A. Horvat)
  • Spiral of Silence in the Social Media Era: A Simulation Approach to the Interplay between Social Networks and Mass Media(D. Sohn)
  • Chambers without Echoes: Computational and Experimental Evidence on Information Propagation in Homogeneous Networks(S. Kim)

Trolls, fake accounts and censorship

(28-May-2019 11:00 AM-12:15 PM, Monroe (Washington Hilton, Concourse Level))

    • If it Behaves Like a Troll, it is a Troll! A Computational Mechanics Approach to Trolling and its Contagion(Q. Sun; M. Hilbert)
    • Issue Competition on Social Media in China: The Interplay Among Media, Verified Users, and Unverified Users(P. Wang)
    • Content Censorship of WeChat Public Account: a five-month preliminary analysis(K. Fu; Y. Tai)
    • “Are they all fake?” A machine learning approach to classify fake followers of US politicians on Twitter(B. Kiessling; T. Drozdzynski; S. Burkhardt; J. Schacht; H. Klimpe)
    • Two Applications of Statistical Relational Learning: Fake News Detection and Congress Voting Patterns(Q. Hao; T. Peng)
    • The Role of Suspended Accounts in Political Discussion on Social Media: Analysis of the 2017 French, UK and German Elections(S. Majo-Vazquez; M. Congosto; T. Nicholls; R. Nielsen)