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Social Computing

Presentation and collaborations

Modern information systems, like Socio-Technical Systems (STS), are getting more and more complex, needing to cope with many stakeholders and with cross-organizational relationships: they require a transition from an individualistic to a societal perspective. Social computing studies the collaborative and interactive aspects of ICT-mediated behavior: social applications perform a social computation which is the sum of the independent contributions of autonomous and heterogeneous parties; they can naturally be formalized based on some notion of norm, in a way that resembles typical mechanisms of the human society.

Social computing finds direct application in social informatics, where social networks are studied, and in legal informatics, where society norms are tackled. It requires the development of new models and methodologies of software engineering and of business processes –that are at the core of system design and of enterprise management systems. To this end, it is necessary to rely on tools developed in computer science, such as knowledge discovery, natural language processing, ontology, multiagent systems, and logic. We study different aspects of Social Computing, that Figure 1 summarizes with respect to two axes: applicative domains and that of tools. The added value of our approach is its twofold interdisciplinarity: both tools level and domains level involve aspects from human and social sciences on a side, and computer science on the other. The added value of our approach is that it is interdisciplinary both at the level of tools and at the level of domains, involving aspects concerning human and social sciences on a side as well as computer science on the other.

More in depth

The covered research themes involve the use of different tools. In alphabetic order:

  • Role, Affordance, STS, Interaction Protocol, Commitment:Traditional approaches to software engineering do not fit the needs of STS for they do not capture the social aspects of computation, like social relationships. Social relationships connect interacting parties, have a normative value, can be verified based just on the parties observable behavior. MASs are a promising paradigm as they are made of autonomous,
    interacting agents. We claim that both agents and social relationships are first-class entities: social relationships are created by executing interaction protocols and provide expectations on the agents’ behavior; social relationships affect the decisions of the agents they involve. From a Software Engineering perspective, the advantage of relying on social relationships is the high decoupling and modularity that system components show.
  • Accountability, Argumentation, Compliance, Conformance, Normative Reasoning:norms are fundamental in modeling social applications –even STS suggest to foresee a specific layer that contains the regulations that norm the system behavior. There is the need of reasoning mechanisms for eliciting information about the agents behavior, and thus about the society. In particular, agents reason about norms to understand which obligations, prohibitions, etc. constrain their behavior, they reason about their own behavior to understand (a priori or at run-time) if/how to conform to the norms, they argue with other agents to reach agreements about how to behave, and, in case of faults/failures, it is necessary to understand which agents are liable for the situation.
  • Process Mining, Run-time Verification, Planning, Diagnosis: cross-organizational business processes and human-oriented workflows are intrinsically social. They implement negotiated agreements among interacting parties. As such, it is important to verify their conformity to the agreements. This can be done statically (conformance) or dynamically (run-time verification). It is also important to mine log data and the like to elicit undocumented processes (a standard in many realities), in order to verify their compliance/conformance to the norms. Instead, when it is necessary to adapt to particular context conditions, it is possible to build a business process on the fly by relying on planning techniques. Finally, diagnosis comes into play when there is the need to find one (or all) possible explanation(s) for the system behavior.
  • Legal Open Data, Legal Ontology, Norm Extraction, Norm Classification: law should be freely and easily accessible. On-line databases and legal knowledge systems are becoming a richer and richer reality. It is important that law representation relies on shared ontologies, to foster understanding, and that it is open, thus simplifying its use and re-use. It is also fundamental to develop tools that allow extracting norm representations from legal text, and to automatically infer whether a norm is influential in a domain of interest.
  • Daily Life Social System: these are systems that support citizens in their every day life. Their realization proposes many challenges, among which: integration of institutional data and social information about the daily life; enhancement of social awareness, self-govenrance, and self-organisation of local communities; realization of ontologies to represent social entities; reasoning mechanisms for multi-facets, multi-purpose and multi-topic knowledge management systems; data visualisation to improve accessibility to information.

Collaborations

Computer Science and Communications research Center, Università del Lussemburgo

CIRSFID, Università di Bologna

School of Computing and Communication, Lancaster University

Multiagent Systems and Service-Oriented Computing Laboratory, North Carolina State University

KBS, Leibniz University Hannover

Nomotika

News


Contacts

Guido Boella

+ 39 011 670 6280

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