Marcella Tambuscio



... is a postdoctoral researcher at Austrian Academy of Sciences in Vienna. Her main research goal is to explore applications for machine learning techniques in the humanities. 

She has a bachelor's degree in Mathematics and a master's degree in Computer Science from University of Pisa. In 2017 she completed her PhD in Computer Science at University of Turin, focusing her research on spreading phenomena in social networks, specially misinformation and fake news diffusion. In her thesis specifically she studied the effectiveness of fact-checking and explored the role of network segregation and gullible communities in the dissemination process of hoaxes. She also explored the influence of social media in the formation of public opinion in online (Twitter) political conversations. Moreover, she collaborated with one of the main Italian banks to analyse their data with network analysis tools.

Her research interests are Network Science, Machine Learning, Data Mining and Visualisation. 


  • Lai, Mirko, Marcella Tambuscio, Viviana Patti, Giancarlo Ruffo, and Paolo Rosso. 2019. Stance polarity in political debates: A diachronic perspective of network homophily and conversations on Twitter. In: Data & Knowledge Engineering124, p. 101738:1-101738:36. doi:10.1016/j.datak.2019.101738.

Publications (Before ACDH)

  • Tambuscio Marcella, Oliveira Diego, Ciampaglia Giovanni, Ruffo Giancarlo, 2018, "Network segregation in a model of misinformation and fact checking", Journal of Computational Social Science (2018) 1: 261.

  • Lai Mirko, Tambuscio Marcella, Patti Viviana, Ruffo Giancarlo, Rosso Paolo, 2017, "Extracting Graph Topological Information and Users Opinion", In: Experimental IR Meets Multilinguality, Multimodality, and Interaction: 8th International Conference of the CLEF Association, CLEF 2017, Dublin, Ireland, September 11-14, 2017, Proceedings. Springer, 2017. p. 112.

  • Tambuscio Marcella, Ruffo Giancarlo, Flammini Alessandro, Menczer Filippo, 2015, "Fact-checking effect on viral hoaxes: A model of misinformation spread in social networks", In Proceedings of the 24th International Conference on World Wide Web (WWW ’15 Companion). ACM, New York, NY, USA, 977-982. DOI: