Alice Mattoni
Scuola Normale Superiore
Italy

Alice Mattoni is Assistant Professor at the Scuola Normale Superiore, where she is the Principal Investigator of the research project PiCME – Political participation in Complex Media Environments: A Multi-Level and Multi-Method Approach. Her research lays at the intersection of media and politics. She did research on the perceptions of the journalistic profession in local newsrooms; activist media practices in precarious workers’ mobilizations; the use of social media during electoral campaigns; and the role of media technologies in pro-democracy and anti-austerity movements, with a special focus on protests in Italy, Spain and Greece. In the past years, Alice collaborated with several international universities, including the University of Toronto (Canada), the University of Technology, Sydney (Australia), the Robert Schuman Centre for Advanced Studies at the European University Institute (Italy), the University of Pittsburgh (USA), Goldsmiths University of London (UK), and Lakehead University (Canada). Amongst other publications, she wrote the monograph Media Practices and Protest Politics. How Precarious Workers Mobilise (Ashgate, 2012) and she co-edited the following volumes: Spreading Protests. Social Movements in Times of Crisis (ECPR Press, 2014), Mediation and Protest Movements (Intellect, 2013), Advances in the Visual Analysis of Social Movements (Emerald, 2013). 

Elena Pavan
University of Trento
Italy

Elena Pavan is Senior Assistant Professor at the Department of Sociology and Social Research of the University of Trento. She holds a degree in Communication Sciences (University of Padova, Italy, 2004) and a PhD in Sociology (University of Trento, 2009). Her most recent research interests pertain to the relationships between collective action/political participation and digital media use. Within this area, she is working interdisciplinary combining technical and social knowledge as well as traditional qualitative and quantitative research methods with digital methods and big data approaches.