Data Science & Social Research
Second international conference on data science and social research
4 February 2019 - University of Milano-Bicocca
5 February 2019 - IULM University
As digital technologies, the internet and social media become increasingly integrated into society, a proliferation of digital footprints of human and societal behaviours are generated in our daily lives. All these data provide opportunities to study complex social systems, by the empirical observation of patterns in large-scale data, quantitative modelling and experiments.
The social data revolution enables not only new business models but it also provides policy makers with better instruments to support their decisions.
This conference aims at stimulating the debate between scholars of different disciplines about the so called “data revolution” in social research. Statisticians, computer scientists and domain experts in social research will discuss the opportunities and challenges of the social data revolution to create a fertile ground for addressing new research problems.
The Data Science and Social Research international conference encourages contributions about:
- new methodological developments to extract social knowledge from large scale data sets;
- new social research about human behaviour and society with large datasets, either mined from various sources (e.g. social media, communication systems) or created via controlled experiments;
- integrated systems to take advantage of new social data sources;
- big data quality issues, both as reformulation of traditional representativeness and validity and as emerging quality aspects such as access constraints, which may produce inequalities.
The themes of the conference are focused on but not restricted to:
- Big data issues in social research
- Data mining
- Data Security
- Decision Support Systems
- Empiricism and Knowledge
- Features of data quality
- Machine learning
- Multivariate analysis
- Pattern recognition
- Sentiment analysis
- Social network data analysis
- Social simulation models
- Statistical knowledge-based methods
- Structural modeling
- Symbolic data analysis
- Textual data analysis
- Crowd computing
- Ethical challenges of technologies, data, algorithms, platforms, and people in the Web
Applications can cover different domains such as Health Care, Finance, Business and Marketing, Customer Journey, Communication, Reputation, Management, Data Journalism, Digital Humanities, Game Studies, and Social inequalities.
Journal special issues
Special issues of the Electronic Journal of Applied Statistical Analysis, the Italian Journal of Applied Statistics and Social Indicators Research will host a selection of papers presented at the conference.