• security
• online social networks
• spam and bot detection
• emergency management
• Twitter
• crisis informatics
• fake news
• social media analysis

The recent proliferation of handheld devices that are equipped with a large number of sensors and communication capabilities, as well as the ubiquitous presence of communication facilities and infrastructures, and the mass diffusion and availability of social networking applications, has created a socio-technical convergence capable of sparking a revolution in the sensing world. One of the most promising and fascinating consequences of this new socio-technical convergence is the possibility to significantly extend, complement, and possibly substitute, conventional sensing by enabling the collection of data through networks of humans. Indeed, these unprecedented sensing and sharing opportunities have enabled situations where individuals not only play the role of sensor operators, but also act as data sources themselves. This spontaneous behavior has driven a new thriving - yet challenging - research field, called social sensing, investigating how human-sourced data can be gathered and used to gain situational awareness in a number of socially relevant domains.
However, the social sensing revolution does not come without costs. Now that each of us can send messages for the entire world to read, or upload pictures for the entire world to see, the amount of real-time information out there far exceeds our cognitive capacity to consume it. Today, we have access to a plethora of blogs, discussion forums, and online social network accounts that provide orders of magnitude increases in the number of news sources. We are thus witnessing to the development of a widening gap between information production and our consumption capacity. Moreover, the reliability of such sources is not guaranteed. Indeed, it has already been demonstrated that observations produced by social sensors might be affected by a number of issues that undermine their usefulness and applicability. Among such issues are the widespread presence of fictitious, malicious, and deceptive social sensors; and the spreading of deceptive content, such as fake news. As a consequence, in order to fully harness this unfolding sensing revolution, we are in dire need of novel algorithms, techniques, and tools that are capable of turning this deluge of messy data into concise, meaningful, and reliable information. The possibility to fruitfully exploit this citizen-sensed stream of big data for novel applications - and ultimately for improving our societies and our everyday life - represents a tantalizing opportunity, counterbalanced by the many challenges related to the assessment of the reliability of such information, as well as its aggregation, summarization, and filtering.
The goal of this thesis is to investigate the two sides of the “social sensing” coin. Thus, the main contributions of this doctoral work are twofold: (i) investigate the problem of credibility and reliability of social sensors; and (ii) explore the opportunities opened up by social sensing for a practically relevant scenario, such as that of emergency management.