Seminars

Starting in the Spring semester 2023, we will begin hosting brownbag seminars with the goal of bringing scholars and graduate students from many disciplines together. We welcome any scholar or researcher with an interest in computational social science methods to attend. Speakers include faculty and graduate students across the Madison research community, especially from the Journalism & Mass Communication, Life Science Communication, Communication Arts, Political Science, and Computer Sciences, and also intelligent researchers from other universities and industry.

Coffee and snacks may be provided for our in-person attendees.

2023 Spring Brownbag Seminars

February 3: Computational Content Analysis for Social Science Research 101

  • Speaker: Zening Duan (Ph.D. student in Mass Communication, UW-Madison)
  • Content: This talk will provide an introduction to the fundamental concepts of content analysis in the computational world, including key steps for designing, implementing, and evaluating a research project. The speaker will also present an overview of the seminar’s content for the spring semester, highlighting topics such as cross-platform data request and validation, social bots, crowdsourcing, and various computational methods including word embeddings, machine learning, computer vision, and network analysis. Attendees can expect to gain a comprehensive understanding of the concepts and practical considerations involved in conducting multimodal content analysis using computational methods.
  • Talk is held on FRIDAY (3:30 pm – 4:30 pm, MCRC Room 5011, register here if join virtually)
  • Materials (Google doc)

February 17: Human discourse, bots, and language generative models (tentative)

  • Speaker: Kai-Cheng Yang (Ph.D Candidate in Informatics, Indiana University Bloomington)
  • Content: TBA
  • Talk is held on FRIDAY (3:30 pm – 5:00 pm, MCRC Room 5011, register link TBA)
  • Materials (link will soon be available)

March 2: Cross-platform data collection and validation (tentative)

  • Speaker: Anqi Shao (Ph.D. student in Mass Communication, UW-Madison)
  • Content: TBA
  • Talk is held on Thursday (3:30 pm – 5:00 pm, MCRC Room 5011, register link TBA)
  • Materials (link will soon be available)

March 24: Human coding, crowdsourcing, and pairwise comparison (tentative)

  • Speaker: Jiaxin Pei (Ph.D Candidate in Information, University of Michigan)
  • Content: TBA
  • Talk is held on FRIDAY (3:30 pm – 5:00 pm, MCRC Room 5011, register link TBA)
  • Materials (link will soon be available)

April 7: Networks analysis (tentative)

  • Speaker: Prof. Marlon Twyman (Annenberg School for Communication and Journalism, USC)
  • Content: TBA
  • Talk is held on FRIDAY (3:30 pm – 5:00 pm, MCRC Room 5011, register link TBA)
  • Materials (link will soon be available)

April 14: Computational research ethics (tentative)

  • Speaker: Prof. Josephine Lukito (Moody College of Communication, UT-Austin)
  • Content: TBA
  • Talk is held on FRIDAY (3:30 pm – 5:00 pm, MCRC Room 5011, register link TBA)
  • Materials (link will soon be available)

April 21: Computer vision (tentative)

  • Speaker: Prof. Jungseock Joo (Department of Communication, UCLA)
  • Content: TBA
  • Talk is held on FRIDAY (3:30 pm – 5:00 pm, MCRC Room 5011, register link TBA)
  • Materials (link will soon be available)

April 28: Vec-tionaries: Development of a word embedding-based optimization approach to extracting moral appeals from text

  • Speaker: Zening Duan (Ph.D. student in Mass Communication, UW-Madison)
  • Content: Social science researchers often study latent content features within messages, such as moral appeals. The challenge for measuring latent features is non-trivial. For example, human coding cannot easily scale up to process large-scale messages or reach conventional intercoder reliability even after repeated training. The rise of computational content analysis has given rise to dictionaries as a low-cost, quick-to-use measurement strategy; that said, dictionaries suffer from known shortcomings, such as insensitivity to context-specific applications. The speaker will introduce a novel computational tool for measuring latent message features, called VecOpt, that integrates information from validated dictionaries with word embeddings through a nonlinear optimization model. The same approach can be transferred to other latent message features and help advance studies on message influence on communicative processes.
  • Talk is held on FRIDAY (3:30 pm – 5:00 pm, MCRC Room 5011, register link to be announced)
  • Materials (link will soon be available)