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Catalyzing social media scholarship with open tools and data

Smith, Marc A.

  • 발행 : 2015.10.31

초록

Social media comprises a vast and consequential landscape that has been poorly mapped and understood. Hundreds of millions of people have eagerly moved many of the conversations and discussions that compose civil society into these services and platforms. There is a need to document and analyze these social spaces for many academic and commercial purposes. The Social Media Research Foundation has engaged a strategy to cultivate better research into the structure and dynamics of social media. The foundation is dedicated to the creation of open tools, open data, and open scholarship related to social media. It has implemented a free and open network collection, analysis, and visualization tool called NodeXL to facilitate social media network research. Using NodeXL a group of researchers has collectively authored a publicly available archive, called the NodeXL Graph Gallery, composed of network data sets and visualizations from users around the world. This site has enabled the aggregation of tens of thousands of network datasets and images. Use of the archive has led to scholarly research results that are based on the wide range and scope of social media data sets available.

키워드

참고문헌

  1. Smith, M., Lee Rainie, Ben Shneiderman, Itai Himelboim. 2014. Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters, Pew Internet Research Center. http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/
  2. Smith, M., Shneiderman, B., Milic-Frayling, N., Rodrigues, E.M., Barash, V., Dunne, C., Capone, T., Perer, A. & Gleave, E. (2009), "Analyzing (social media) networks with NodeXL", In C&T '09: Proc. fourth international conference on Communities and Technologies. New York, NY, USA., pp. 255-264. ACM.
  3. Clauset, A., Newman, M. E. J., & Moore, C. (2004). Finding community structure in very large networks. Physical Review E, 70(6), 066111. https://doi.org/10.1103/PhysRevE.70.066111
  4. Harel, D., & Koren, Y. (2001). A fast multi-scale method for drawing large graphs. In 8th International Symposium on Graph Drawing, 1984 Lecture Notes in Computer Science, 183-196.
  5. Eduarda Mendes Rodrigues, Natasa Milic-Frayling, Marc Smith, Ben Shneiderman, Derek Hansen, Group-in-a-box Layout for Multi-faceted Analysis of Communities. IEEE Third Interna-tional Conference on Social Computing, October 9-11, 2011. Boston, MA

피인용 문헌

  1. Theories in communication science: a structural analysis using webometrics and social network approach vol.108, pp.2, 2016, https://doi.org/10.17477/jcea.2015.14.2.087
  2. Unveiling cultures in emergency response communication networks on social media: following the 2016 Louisiana floods pp.1573-7845, 2017, https://doi.org/10.17477/jcea.2015.14.2.087
  3. Identification of future signal based on the quantitative and qualitative text mining: a case study on ethical issues in artificial intelligence pp.1573-7845, 2017, https://doi.org/10.17477/jcea.2015.14.2.087
  4. YouTubers’ networking activities during the 2016 South Korea earthquake pp.1573-7845, 2017, https://doi.org/10.17477/jcea.2015.14.2.087
  5. Climate change and YouTube: Deliberation Potential in Post-video Discussions pp.1752-4040, 2017, https://doi.org/10.17477/jcea.2015.14.2.087