GalaxyScope: Finding the “Truth of Tribes” on Social Media

Part of the Studies on Entrepreneurship, Structural Change and Industrial Dynamics book series (ESID)


This paper introduces GalaxyScope, a novel system to distinguish different interpretations of “truth” for different virtual tribes. It extracts the tribes from Wikipedia through analyzing its categories “Ideologies”, “Lifestyles”, and “Culture”, leading to tribes such as “capitalism”, “socialism”, and “liberalism”. It then calculates the most influential “tribe leaders” through their association on Wikipedia with these concepts. To score their influence in Wikipedia, we use a novel metric we call “reach2” which measures how many people somebody can reach within two degrees of separation on Wikipedia living people pages. It subsequently calculates the vocabulary on Twitter of the tribe leaders, and uses these words to automatically assign individuals to tribes, as well as calculating the relevance of text documents such as tweets or news items for each tribe.


  1. Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election.
  2. Becker, H., Naaman, M., & Gravano, L. (2011). Beyond trending topics: Real-world event identification on Twitter. ICWSM, 11, 438–441.Google Scholar
  3. Gloor, P. (2017). Sociometrics and human relationships: Analyzing social networks to manage brands, predict trends, and improve organizational performance. London: Emerald.CrossRefGoogle Scholar
  4. Gloor, P., Marcos, J., de Boer, P., Fuehres, H., Lo, W., & Nemoto, K. (2016, October). Cultural anthropology through the lens of Wikipedia In X. Fu, J.-D. Luo, M. Boos (Eds.), Social network analysis: Interdisciplinary approaches and case, Chapter 10. Boca Raton, FL: CRC Press, Taylor & Francis Group. isbn 1498736645.Google Scholar
  5. Gupta, A., Lamba, H., & Kumaraguru, P. (2013a). $1.00 per RT #BostonMarathon #PrayForBoston: Analyzing fake content on Twitter, 2013. APWG eCrime Researchers Summit, San Francisco, CA, pp. 1–12.Google Scholar
  6. Gupta, A., Lamba, H., Kumaraguru, P., & Joshi, A. (2013b). Faking Sandy: Characterizing and identifying fake images on Twitter during Hurricane Sandy. In Proceedings of the 22nd International Conference on World Wide Web (WWW’13 Companion) (pp. 729–736). ACM, New York, NY, USA.Google Scholar
  7. Gupta, A., Kumaraguru, P., Castillo, C., & Meier, P. (2014). TweetCred: Real-time credibility assessment of content on Twitter. In L. M. Aiello & D. McFarland (Eds.), Social informatics. SocInfo 2014. Lecture notes in computer science (Vol. 8851). Cham: Springer.Google Scholar
  8. Petrovic, S., Osborne, M., McCreadie, R., Macdonald, C., Ounis, I., & Shrimpton, L. (2013, June). Can Twitter replace newswire for breaking news? In Seventh International AAAI Conference on Weblogs and Social Media.Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Galaxyadvisors AGAarauSwitzerland
  2. 2.MIT Center for Collective IntelligenceCambridgeUSA

Personalised recommendations