An introduction to the special issue on cross-community mining

People now live in heterogeneous social communities within cyber-physical spaces—both online communities (e.g., Flickr, Google+, LinkedIn) and social networks where digital content is exchanged, and opportunistic or offline communities that exploit opportunistic relationships between pairs of networked devices to exchange content (built on mobile ad hoc networking techniques) [1]. These communities have different technical features which lead to distinct kinds of interaction—such as patterns of comments and likes in online communities and co-location in offline communities, or issues of friendship, trust and influence in online communities and social popularity, and movement patterns in offline communities. We further envision the rapid development of cross-space communities in recent years, which try to bridge the gap between human interactions in the physical world and virtual world (by merging social elements in online social networks with physical contexts in offline communities). Significant examples include: location-based social networks (LBSNs, e.g., FourSquare, Jiepang) [2], which interlink online human interaction with offline check-ins; event-based social networks (EBSNs, e.g., MeetUp), which try to build the link between physical and online events [3]

Inclusive Education: The Forms of Violation of Children’s Rights and School Dropouts in the Kadey Division: East Region of Cameroon

Article 8 of the African Aspirations for 2063 stipulates that the African people are confident that their countries have the ability and competence to realize or accomplish their full potential in development, culture, and peace. The vast majority of countries in Africa have worked toward establishing flourishing, inclusive, successful and prosperous societies by eradicating any forms of violation of children’s rights (African Union Commission, 2015). Nevertheless, violation of children’s rights remains present in most developing countries including the country of Cameroon. This research aims to explore the forms of violation of children’s rights having a dramatic incident in school attendance in the Kadey Division of Cameroon, East Region of Cameroon. This research work is inductive, values bias and uses the grounded theory of the qualitative method approach. 15 participants have been selected from 3 major focused groups of different stakeholders in the Kadey Division, East Region of Cameroon. The theoretical saturation code was used to explain the relevance of the sample size. Data were examined using the open, axial, and selective coding processes. The results were tested for internal and external validity based on credibility, dependability, conformability, and transferability consideration. The philosophical focused on subjectivism ontology and interpretivism perspective. The study is an investigative case study model. The study showed that the forms of violation of children’s rights in the Kadey division include the recruitment and use of children, the denial of humanitarian access, the sexual violence against children and the killing and hurting of children. This study encourages school leaders in the Kadey Division to acknowledge that schools are not meant to function apart from the local community. Promoting strong collaborative work ethics between the major educational stakeholders may help prevent and reduce violence against children within and outside the school milieu and therefore duplicate school attendance. (UNICEF Regional Office for South Asia, 2016)

Argumentation Mining in User-Generated Web Discourse

The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theories and argumentation phenomena encountered in actual data by adapting an argumentation model tested in an extensive annotation study. (iii) We create a new gold standard corpus (90k tokens in 340 documents) and experiment with several machine learning methods to identify argument components. We offer the data, source codes, and annotation guidelines to the community under free licenses. Our findings show that argumentation mining in user-generated Web discourse is a feasible but challenging task.Comment: Cite as: Habernal, I. & Gurevych, I. (2017). Argumentation Mining in User-Generated Web Discourse. Computational Linguistics 43(1), pp. 125-17

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems