Mirko Lai

Debate on political reforms in Twitter: A hashtag-driven analysis of political polarization

Political debates about a reform may sparkle national controversies, by leading members of the community to polarize their opinions and sentiment about the topic addressed. With the rise of social media like Twitter users are encouraged to voice and share their strong and polarized views and in general people are exposed to broader viewpoints than they were before. The large amount of user-generated social data available is a great opportunity to investigate the communicative behaviors emerging in the context of such political debates and to shed some light on the way communities of users with different roles in the society and different political sentiment interact. In this paper we focussed on communications in Twitter around the reform of marriage in France in 2012 and 2013 - “Le Mariage Pour Tous” - which had been the subject of debate and controversy. We collected a corpus of tweets tagged by the hashtag #mariagepourtous, created to mark the messages about the reform. We applied different kinds of analysis on our dataset based on linguistic and non linguistic features of the observed data in order to investigate the communicative behavior in using subjective and evaluative language on a political topic. The analysis leaded also to reflect on the impact of different typologies of users involved in the virtual debate which included both political messages created by media organizations and by other individual users, from ordinary citizens to politicians or celebrities.

Designing a personal informatics system for users without experience in self-tracking: a case study

ABSTRACT Thanks to the advancements in ubiquitous and wearable technologies, Personal Informatics (PI) systems can now reach a larger audience of users. However, it is not still clear whether this kind of tool can fit the needs of their daily lives. Our research aims at identifying specific barriers that may prevent the widespread adoption of PI and finding solutions to overcome them. We requested users without competence in self-tracking to use different PI instruments during their daily practices, identifying five user requirements by which to design novel PI tools. On such requirements, we developed a new system that can stimulate the use of these technologies, by enhancing the perceived benefits of collecting personal data. Then, we explored how naïve and experienced users differently explore their personal data in our system through a user trial. Results showed that the system was successful at helping individuals manage and interpret their own data, validated the usefulness of the requirements found and inspired three further design opportunities that could orient the design of future PI systems.

The role of the network of matches on predicting success in table tennis

ABSTRACT The influence of training, posture, nutrition or psychological attitudes on an athlete’s career is well described in literature. An additional factor of success that is widely recognized as crucial is the network of matches that an athlete plays during a season. The hypothesis is that the quality of a player’s opponents affects her long-term ranking and performance. Even though the relevance of these factors is widely recognized as important, a quantitative characterization is missing. In this paper, we try to fill this gap combining network analysis and machine learning to estimate the contribution of the network of matches in predicting an athlete’s success. We consider all the official games played by the Italian table tennis players between 2011 and 2016. We observe that the matches network shows scale-free behavior, typical of several real-world systems, and that different structural properties are positively correlated with the athletes’ performance (Spearman , p-value ). Using these findings, we implement three different tasks, such as talent identification, performance and ranking prediction. Results shows consistently that machine learning approaches are able to predict players’ success and that the topological features play an effective role in increasing their predictive power.