A critical review of the role of repair cafés in a sustainable circular transition

Extending the useful life of consumer products is a critical element in the circular economy. Although commercial repair is an established part of the global economy, the repair is often conducted informally. This means that non-commercial repair ecosystems exist, including the international network of repair cafés, spreading worldwide to over 2000 repair cafés in 37 countries (April 2021). As the first review on this topic, this article investigates and gains more knowledge about repair cafés, and critically assesses their role as a sustainability initiative, i.e., how the concept may translate into a broader sustainability context. A systematic literature review (2010–2020) was conducted, including 44 articles in descriptive and content analyses. The bibliometric data revealed an increase in the number of publications on repair cafés, particularly over the last four years, indicating that repair cafés as a research topic have started to gain attention, and this is likely to grow in numbers. However, the significant number of different places of publication indicates that this is not (yet) a well-established field with defined research channels. The content analysis revealed that the concept has spread to a range of different contexts, beyond the original scope, influencing the mindset and acts of a broad field of practitioners. This indicates a wide range of possibilities for the expansion of the concept of repair cafés, bringing different expectations on calling into question the future role of repair cafés. However, the aims of the people involved in repair cafés span from the altruistic and strategic, over personal gains, to critical consumer, financial and educational aims. This may challenge repair cafés’ future role(s), i.e., ambitions set by the international organisation of repair cafés. Notably, the ambition for actors at the micro-level is to feed in data on repair and achieve ‘collaborative repair’, as the aims of the people involved are complex, and their expectations lack alignment, both vertically and horizontally

A Data Mining Toolbox for Collaborative Writing Processes

Collaborative writing (CW) is an essential skill in academia and industry. Providing support during the process of CW can be useful not only for achieving better quality documents, but also for improving the CW skills of the writers. In order to properly support collaborative writing, it is essential to understand how ideas and concepts are developed during the writing process, which consists of a series of steps of writing activities. These steps can be considered as sequence patterns comprising both time events and the semantics of the changes made during those steps. Two techniques can be combined to examine those patterns: process mining, which focuses on extracting process-related knowledge from event logs recorded by an information system; and semantic analysis, which focuses on extracting knowledge about what the student wrote or edited. This thesis contributes (i) techniques to automatically extract process models of collaborative writing processes and (ii) visualisations to describe aspects of collaborative writing. These two techniques form a data mining toolbox for collaborative writing by using process mining, probabilistic graphical models, and text mining. First, I created a framework, WriteProc, for investigating collaborative writing processes, integrated with the existing cloud computing writing tools in Google Docs. Secondly, I created new heuristic to extract the semantic nature of text edits that occur in the document revisions and automatically identify the corresponding writing activities. Thirdly, based on sequences of writing activities, I propose methods to discover the writing process models and transitional state diagrams using a process mining algorithm, Heuristics Miner, and Hidden Markov Models, respectively. Finally, I designed three types of visualisations and made contributions to their underlying techniques for analysing writing processes. All components of the toolbox are validated against annotated writing activities of real documents and a synthetic dataset. I also illustrate how the automatically discovered process models and visualisations are used in the process analysis with real documents written by groups of graduate students. I discuss how the analyses can be used to gain further insight into how students work and create their collaborative documents

Criminal Group Dynamics and Network Methods

Value – Network methods provide a means to revisit and extend theories of crime and delinquency with a focus on social structure. The unique affinity between group dynamics and network methods highlights immense opportunities for expanding the knowledge of collective trajectories

How change agents and social capital influence the adoption of innovations among small farmers: Evidence from social networks in rural Bolivia

"This paper presents results from a study that identified patterns of social interaction among small farmers in three agricultural subsectors in Bolivia—fish culture, peanut production, and quinoa production—and analyzed how social interaction influences farmers' behavior toward the adoption of pro-poor innovations. Twelve microregions were identified, four in each subsector, setting the terrain for an analysis of parts of social networks that deal with the diffusion of specific sets of innovations. Three hundred sixty farmers involved in theses networks as well as 60 change agents and other actors promoting directly or indirectly the diffusion of innovations were interviewed about the interactions they maintain with other agents in the network and the sociodemographic characteristics that influence their adoption behavior. The information derived from this data collection was used to test a wide range of hypotheses on the impact that the embeddedness of farmers in social networks has on the intensity with which they adopt innovations. Evidence provided by the study suggests that persuasion, social influence, and competition are significant influences in the decisions of farmers in poor rural regions in Bolivia to adopt innovations. The results of this study are meant to attract the attention of policymakers and practitioners who are interested in the design and implementation of projects and programs fostering agricultural innovation and who may want to take into account the effects of social interaction and social capital. Meanwhile, scholars of the diffusion of innovations may find evidence to further embrace the complexity and interdependence of social interactions in their models and approaches." from Author's AbstractSocial networks, Agricultural innovation, Change agent, Social capital,

On the discovery of social roles in large scale social systems

The social role of a participant in a social system is a label conceptualizing the circumstances under which she interacts within it. They may be used as a theoretical tool that explains why and how users participate in an online social system. Social role analysis also serves practical purposes, such as reducing the structure of complex systems to rela- tionships among roles rather than alters, and enabling a comparison of social systems that emerge in similar contexts. This article presents a data-driven approach for the discovery of social roles in large scale social systems. Motivated by an analysis of the present art, the method discovers roles by the conditional triad censuses of user ego-networks, which is a promising tool because they capture the degree to which basic social forces push upon a user to interact with others. Clusters of censuses, inferred from samples of large scale network carefully chosen to preserve local structural prop- erties, define the social roles. The promise of the method is demonstrated by discussing and discovering the roles that emerge in both Facebook and Wikipedia. The article con- cludes with a discussion of the challenges and future opportunities in the discovery of social roles in large social systems

Reviewing Radicalization Research Using a Network Approach

In an effort to discern determinants of political radicalization, scholars have discussed and investigated a considerable number of personal or contextual constructs. Yet the existing literature reviews on this topic have mainly focused on specific data sources and research approaches (e.g., survey research), whereas an integrative overview is still missing. This study provides a systematic review of 57 published studies while particularly focusing on differences in the prevalence of considered determinants across research approaches (i.e., survey approaches, experimental approaches, and digital trace data approaches). As an innovative approach to systematic review, we apply a network approach for analyzing the most prevalent constructs and related hypotheses in the literature. Network analysis is particularly useful in this context because, it allows the visualization of the structure of constructs and hypotheses proposed in the field as well as the identification of crucial concepts. The review reveals differences across empirical approaches and closes with a discussion of over- and underresearched constructs, their generalizability across research approaches, and potentials for future research. We conclude by recommending a stronger integration of constructs and perspectives as well as a more rigid consideration of causal inference. Editorial Note: This article underwent a post-publication review and revision in response to criticism about problematic use of a closely related and previously published article. The corrected version was uploaded August 4, 2020.  Authors' Correction Note:Reviewing Radicalization Research Using a Network ApproachVeronika Batzdorfer & Holger Steinmetz In the corrected article, the authors respond to criticism regarding similarities in the literature search process and insufficient connections between a recent meta-analysis (Wolfowicz, Litmanovitz, Weisburd, & Hasisi, 2019) and the present paper. Although the present paper cited Wolfowicz et al. (2019) several times, these linkages were not presented well enough. In the corrected paper, these connections are emphasized in the following way:1) In the introduction, we note that the review builds on the meta-analysis by Wolfowicz et al. (2019) and stress the add-on value of our paper and the possibilities of fruitfully integrating both studies2) In the method section, we note the similarities of both reviews in the search process, data bases, and search terms3) In the discussion section, we added a discussion in which we integrate results of bothDue to the correction, readers are now better informed about similarities and differences of our studies.Wolfowicz, M., Litmanovitz, Y., Weisburd, D., & Hasisi, B. (2019). A field-wide systematic review and meta-analysis of putative risk and protective factors for radicalization outcomes. Journal of Quantitative Criminology, 1-41

Who will lead and who will follow: Identifying Influential Users in Online Social Networks - A Critical Review and Future Research Directions

Along with the explosive growth of the phenomenon Online Social Networks (OSN), identifying influential users in OSN has received a great deal of attention in recent years. However, the development of practical approaches for identifying them is still in its infancy. By means of a structured literature review, the authors analyze and synthesize the publications particularly from two perspectives. From a research perspective, they find that existing approaches mostly build on users’ connectivity and activity but hardly consider further characteristics of influential users. Moreover, they outline two major research streams. It becomes apparent that most marketing-oriented articles draw on real-world data of OSN, while more technology-oriented papers rather have a theoretical approach and mostly evaluate their artifacts by means of formal proofs. The authors find that a stronger collaboration between the scientific Business and Information Systems Engineering (BISE) and Marketing communities could be mutually beneficial. With respect to a practitioner’s perspective, they compile advice on the practical application of approaches for the identification of influential users. It is hoped that the results can stimulate and guide future research

Gender Disparities in Science? Dropout, Productivity, Collaborations and Success of Male and Female Computer Scientists

Scientific collaborations shape ideas as well as innovations and are both the substrate for, and the outcome of, academic careers. Recent studies show that gender inequality is still present in many scientific practices ranging from hiring to peer-review processes and grant applications. In this work, we investigate gender-specific differences in collaboration patterns of more than one million computer scientists over the course of 47 years. We explore how these patterns change over years and career ages and how they impact scientific success. Our results highlight that successful male and female scientists reveal the same collaboration patterns: compared to scientists in the same career age, they tend to collaborate with more colleagues than other scientists, seek innovations as brokers and establish longer-lasting and more repetitive collaborations. However, women are on average less likely to adapt the collaboration patterns that are related with success, more likely to embed into ego networks devoid of structural holes, and they exhibit stronger gender homophily as well as a consistently higher dropout rate than men in all career ages