Conducting Research on Twitter-Based Communication Phenomena: Why Not?
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Conducting Research on Twitter-Based Communication Phenomena: Why Not?

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Conducting Research on Twitter-Based Communication Phenomena: Why Not? Conducting Research on Twitter-Based Communication Phenomena: Why Not? Presentation Transcript

  • Presentation Outline 1. Why study social media? 2. The rise of a new research model; 3. Collecting and archiving the data; 4. Analyzing the data; 5. Making sense of the data; 6. Conclusion.
  • Why study social media? Sources: Pew Research Center
  • Why study social media? Sources: Pew Research Center
  • Why study social media? Sources: Raynauld,2013; Khang, Ki et al. 2012; Kietzmann, Silvestre et al. 2012; Raynauld and Greenberg under eveluation • Traditional media vs. Conventional media; • Impact of social media on individuals and society as a whole: • Production, categorization, and mass circulation of content; • Acquisition of information; • Structure of social interactions; • Community-building; • Self-presentation; • Etc.
  • Why study social media? Source: Raynauld and Greenberg, under evaluation. • Twitter as a research object: • Low-cost micro-blogging service: • Time; • Technical resources and skills; • Financial resources; • Posts of up to 140 characters; • Wide-ranging content; • Internal community-building functions; • Few ethical considerations (public data); • Flexibility for researchers.
  • Why study social media? Ethical considerations • Twitter as a research tool : • Active participant approach to research: • Decentralized circulation of surveys and other questionnaires (snowball sampling):
  • The rise of a new research model • A new way to do business: • Proactive vs. Reactive research: • Constant monitoring of the social mediascape; • Identifying research opportunities (e.g. “What’s trending,” events, etc.); • Adaptivity and creativity. • Rapidly-evolving nature of social media research: • Constant rise of new social media channels; • Social media in “perpetual beta”? • Evolution of data collection and analytical tools; • Importance for researchers to remain flexible. Are higher education institutions ready?
  • Collecting and archiving the data Sources: Raynauld, Giasson et al. 2011; Raynauld 2013; Raynauld, Lalancette et al. 2014 • Small data vs. Big data; • The importance of sampling: • Hashtags; • Twitter accounts; • Etc. • Type of data collected: • Name, picture, and other information relating to tweeters; • Time and date of publication of tweets; • Content of tweets; • Social interactive functions: • @replies; • Retweets. • Etc. Factors influencing the sampling: • Research question; • Objectives; • Access to resources; • Capabilities of archiving platform.
  • Collecting and archiving the data Sources: Raynauld, Giasson et al. 2011; Raynauld, Lalancette et al. 2014 – Special thanks to Valérie Bélair-Gagnon. • Data collection and archiving tools: • In-house options: • Resource-intensive; • Less flexibility; • Challenges linked to the “perpetual beta” nature of social media (e.g. API); • Require a programmer on staff. • Open-source alternatives: • ScraperWiki; • Tweet Archivist; • SnapBird; • Twitonomy; • Etc.
  • Collecting and archiving the data • Screenshot of ScraperWiki:
  • Analyzing the data Sources: Raynauld, Giasson et al. 2011; Raynauld, Lalancette et al. 2014 • Conventional approaches: • Quantitative content analysis (mostly descriptive): • Number of tweets; • Content of posts; • Etc. • Qualitative content analysis: • Function of tweets; • Function of the content of tweets: • Photos; • Videos; • Hyperlinks; • Geographic locations. • Etc. Little qualitative work on Twitter-based communication phenomena so far.
  • Analyzing the data Sources: Raynauld 2013; Turcotte and Raynauld 2014 • Innovative approaches: • Network analysis (@replies): Number of @replies 877 Number of nodes 654 Number of edges 648 Average degree 0.991 December 14, 2009 to December 20, 2009 Node Edge
  • Analyzing the data • Innovative approaches: • Sentiment analysis: Source: Raynauld and Greenberg under evaluation
  • Making sense of the data • Factors influencing this process: • Research questions; • Research objectives; • Type of analysis; • Etc. • Importance of interdisciplinary research • The decline of “silo” approaches to research; • The rise of new research models: • Flexibility; • Collaboration across disciplines; • Teamwork.
  • Conclusion • Challenges to social media research: • Investigative approaches tailored for the study of traditional mass media need to be revisited; • “Big data”; • Etc. • New research model challenging traditional methods; • Teamwork; • Pooling of expertise; • Avoid “research in silo.” • Many opportunities: • New research questions; • New methodologies; • Flexibility; • Etc. Sources: Raynauld and Greenberg under evaluationl Raynauld, Lalancette et al. 2014
  • Conclusion • Potential social media-related research in public relations and other fields relating to communication studies: • Crisis management; • Branding; • Political communication; • Advocacy; • Social marketing; • Etc. Sources: Raynauld and Greenberg under evaluationl Raynauld, Lalancette et al. 2014 Any ideas?
  • Conclusion • What am I thinking about? • Hyperlocal journalism; • Transformation of political campaigning: • Hyperlocal information dispersion and organizing; • New form of polling based on geolocation; • Concerns; • Opinions; • Etc. • Redefinition of the relationship between elected officials and constituents; • Etc. Sources: Raynauld and Greenberg under evaluationl Raynauld, Lalancette et al. 2014
  • QUESTIONS
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