Social web services management

As part of our ongoing work on social-intensive Web services, also referred to as social Web services, different types of networks that connect them together are developed. These networks include collaboration, substitution, and competition, and permit the addressing of specific issues related to Web service use such as composition, discovery, and high-availability. Social is embraced because of the similarities of situations that Web services run into at run time with situations that people experience daily. Indeed, Web services compete, collaborate, and substitute. This is typical to what people do. This chapter sheds light on some criteria that support Web service selection of a certain network to sign up over another. These criteria are driven by the security means that each network deploys to ensure the safety and privacy of its members from potential attacks. When a Web service signs up in a network, it becomes exposed to both the authority of the network and the existing members in the network as well. These two can check and alter the Web service\u27s credentials, which may jeopardize its reputation and correctness levels

Social web services management

As part of our ongoing work on social-intensive Web services, also referred to as social Web services, different types of networks that connect them together are developed. These networks include collaboration, substitution, and competition, and permit the addressing of specific issues related to Web service use such as composition, discovery, and high-availability. Social is embraced because of the similarities of situations that Web services run into at run time with situations that people experience daily. Indeed, Web services compete, collaborate, and substitute. This is typical to what people do. This chapter sheds light on some criteria that support Web service selection of a certain network to sign up over another. These criteria are driven by the security means that each network deploys to ensure the safety and privacy of its members from potential attacks. When a Web service signs up in a network, it becomes exposed to both the authority of the network and the existing members in the network as well. These two can check and alter the Web service\u27s credentials, which may jeopardize its reputation and correctness levels

Specifying and implementing social Web services operation using commitments

This paper discusses the specification and development of social Web services using commitments. Social Web services establish and maintain networks of contacts, count on their (privileged) contacts when needed, form with other peers strong and long lasting collaborative groups, and know with whom to partner so that ontology reconciliation is minimized. To guarantee the proper execution of these operations, social Web services need to comply with the regulations of the social networks in which they have signed up. This compliance is verified using commitments. Two types of commitments are identified: social and business. The former connect Web services to social networks. And the latter connect social Web services to composite social Web services. A proof-of-concept system to detect commitment violations is, also, discussed in this paper. © 2012 ACM

Analyzing social web services\u27 capabilities

© 2015 IEEE. This paper looks into ways of supporting social Web services react to the behaviors that their peers expose at run time. Examples of behaviors include selfishness and unfairness. These reactions are associated with actions packaged into capabilities. A capability allows a social Web service to stop exchanging private details with a peer and/or to suspend collaborating with another peer, for example. The analysis of capability results into three types referred to as functional (what a social Web service does), non-functional (how a social Web service runs), and social (how a social Web service reacts to peers). To avoid cross-cutting concerns among these capabilities aspect-oriented programming is used for implementing a system

Commitments to regulate social web services operation

This paper discusses how social Web services are held responsible for the actions they take at run time. Compared to (regular) Web services, social Web services perform different actions, for instance establishing and maintaining networks of contacts and forming with some privileged contacts strong and long lasting collaborative groups. Assessing these actions\u27 outcomes, to avoid any violation, occurs through commitments that the social Web services are required to bind to. Two types of commitments are identified: social commitments that guarantee the proper use of the social networks in which the social Web services sign up, and business commitments that guarantee the proper development of composite Web services in response to users\u27 requests. Detecting commitment violation and action prohibition using monitoring results in imposing sanctions on the \u27guilty\u27 social Web services and taking corrective actions. A system for commitment management in terms of definition, binding, monitoring, and violation detection is also discussed in this paper. © 2013 IEEE

Reputation-based composition of social web services

Social Web Services (SWSs) constitute a novel paradigm of service-oriented computing, where Web services, just like humans, sign up in social networks that guarantee, e.g., better service discovery for users and faster replacement in case of service failures. In past work, composition of SWSs was mainly supported by specialised social networks of competitor services and cooperating ones. In this work, we continue this line of research, by proposing a novel SWSs composition procedure driven by the SWSs reputation. Making use of a well-known formal language and associated tools, we specify the composition steps and we prove that such reputation-driven approach assures better results in terms of the overall quality of service of the compositions, with respect to randomly selecting SWSs. © 2014 IEEE

A MOF-based social web services description metamodel

© Copyright 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved. To promote and support the development and use of social Web services by the IT community on the Web, both social Web service-based applications and their support platforms should evolve independently from each other while sharing a common model that represents the characteristics of these social Web services. To achieve this duality, this paper proposes a model-driven approach. First, the approach identifies a social Web service\u27s properties. Then a Meta-Object-Facility (MOF)-based social Web services description metamodel is developed. Finally, a prototype illustrates how the MOF-based metamodel is used

Using incentives to analyze social web services’ behaviors

© Springer International Publishing Switzerland 2015. This paper discusses how incentives allow social networks to attract more members and reward those that are honest by retaining them. These members referred to as social Web services process users’ requests in return for a certain usage fee and also expose certain behaviors in return of the incentives they receive. The usage fee is linked to a performance level that the social Web service needs to maintain at run time. In the case of any discrepancy between the usage fee and performance level the social Web service is expected to compensate users. However the compensation might not always take place. Simulation results illustrate why honesty is rewarding for social Web services, which has a positive impact on both their performance and the performance of the networks to which they belong

Do altmetrics work? Twitter and ten other social web services

Altmetric measurements derived from the social web are increasingly advocated and used as early indicators of article impact and usefulness. Nevertheless, there is a lack of systematic scientific evidence that altmetrics are valid proxies of either impact or utility although a few case studies have reported medium correlations between specific altmetrics and citation rates for individual journals or fields. To fill this gap, this study compares 11 altmetrics with Web of Science citations for 76 to 208,739 PubMed articles with at least one altmetric mention in each case and up to 1,891 journals per metric. It also introduces a simple sign test to overcome biases caused by different citation and usage windows. Statistically significant associations were found between higher metric scores and higher citations for articles with positive altmetric scores in all cases with sufficient evidence (Twitter, Facebook wall posts, research highlights, blogs, mainstream media and forums) except perhaps for Google+ posts. Evidence was insufficient for LinkedIn, Pinterest, question and answer sites, and Reddit, and no conclusions should be drawn about articles with zero altmetric scores or the strength of any correlation between altmetrics and citations. Nevertheless, comparisons between citations and metric values for articles published at different times, even within the same year, can remove or reverse this association and so publishers and scientometricians should consider the effect of time when using altmetrics to rank articles. Finally, the coverage of all the altmetrics except for Twitter seems to be low and so it is not clear if they are prevalent enough to be useful in practice