Researching Visual Social Media Platforms

dc.contributor.authorMurthy, Dhiraj
dc.date.accessioned2020-01-28T14:01:31Z
dc.date.available2020-01-28T14:01:31Z
dc.date.issued2020-01-28
dc.descriptionDhiraj Murthy is an Associate Professor of Journalism and Sociology at the University of Texas at Austin. He founded and directs the Computational Media Lab there. Murthy’s research explores social media, computational social science, race/ethnicity, qualitative/mixed methods, and disasters. Dr. Murthy has edited 3 journal special issues and authored over 60 articles, book chapters, and papers. Murthy wrote the first scholarly book about Twitter (second edition published by Polity Press, 2018). He is currently funded by the National Science Foundation’s Civil, Mechanical and Manufacturing Innovation (CMMI) Division for pioneering work on using the social media networks of journalists for damage reconnaissance during Hurricane Florence. Dr. Murthy’s work also uniquely explores the potential role of social technologies in diversity and community inclusion.
dc.description.abstractWith the meteoric rise of Instagram, Snapchat and YouTube, it is clear that image- and video- based platforms have become tremendously important to our social, political, and economic lives. However, there are unique challenges associated with data collection and analysis on visual social media platforms. This workshop explores the following questions in detail: How do we integrate and weigh Big Data questions with more in-depth contextualized analysis of social media content? How do we categorize textual and visual content, addressing issues of ontology? How can we scale small data to big data in visual spaces? Ultimately, it is argued that image/video data produced and consumed on social media has real value in helping us understand the social experience of everyday and profound events, but studying these types of data often requires innovations in theory and methods. Hands-on methods work will involve participants collecting data from YouTube and understanding structured metadata and unstructured data involving visual content.
dc.identifier.urihttps://hdl.handle.net/2022/25138
dc.language.isoen
dc.publisherIndiana University Workshop in Methods
dc.relation.urihttps://purl.dlib.indiana.edu/iudl/media/q57n69s741
dc.rightsThis work may be protected by copyright unless otherwise stated.
dc.titleResearching Visual Social Media Platforms
dc.typePresentation

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