Polarization of coalitions in an agent-based model of political discourse

Political discourse is the verbal interaction between political actors in a policy domain. This article explains the formation of polarized advocacy or discourse coalitions in this complex phenomenon by presenting a dynamic, stochastic, and discrete agent-based model based on graph theory and local optimization. In a series of thought experiments, actors compute their utility of contributing a specific statement to the discourse by following ideological criteria, preferential attachment, agenda-setting strategies, governmental coherence, or other mechanisms. The evolving macro-level discourse is represented as a dynamic network and evaluated against arguments from the literature on the policy process. A simple combination of four theoretical mechanisms is already able to produce artificial policy debates with theoretically plausible properties. Any sufficiently realistic configuration must entail innovative and path-dependent elements as well as a blend of exogenous preferences and endogenous opinion formation mechanisms

Not all the bots are created equal:the Ordering Turing Test for the labelling of bots in MMORPGs

This article contributes to the research on bots in Social Media. It takes as its starting point an emerging perspective which proposes that we should abandon the investigation of the Turing Test and the functional aspects of bots in favor of studying the authentic and cooperative relationship between humans and bots. Contrary to this view, this article argues that Turing Tests are one of the ways in which authentic relationships between humans and bots take place. To understand this, this article introduces the concept of Ordering Turing Tests: these are sort of Turing Tests proposed by social actors for purposes of achieving social order when bots produce deviant behavior. An Ordering Turing Test is method for labeling deviance, whereby social actors can use this test to tell apart rule-abiding humans and rule-breaking bots. Using examples from Massively Multiplayer Online Role-Playing Games, this article illustrates how Ordering Turing Tests are proposed and justified by players and service providers. Data for the research comes from scientific literature on Machine Learning proposed for the identification of bots and from game forums and other player produced paratexts from the case study of the game Runescape

Data Innovation for International Development: An overview of natural language processing for qualitative data analysis

Availability, collection and access to quantitative data, as well as its limitations, often make qualitative data the resource upon which development programs heavily rely. Both traditional interview data and social media analysis can provide rich contextual information and are essential for research, appraisal, monitoring and evaluation. These data may be difficult to process and analyze both systematically and at scale. This, in turn, limits the ability of timely data driven decision-making which is essential in fast evolving complex social systems. In this paper, we discuss the potential of using natural language processing to systematize analysis of qualitative data, and to inform quick decision-making in the development context. We illustrate this with interview data generated in a format of micro-narratives for the UNDP Fragments of Impact project

Evaluating Ecosystem Investments

This report focuses on what was learned about best practices for evaluating the effects of ecosystem investments along with examples of how others are using these practicesin their work.MethodologyThree research questions guided this engagement:What are the new / best practices in evaluating the effects of ecosystem invest­ments?Which organizations are evaluating these investments well? What can they teach us?What relevant outcomes and indicators could Omidyar Network use to evaluate its ecosystem investments?To answer these questions, FSG conducted the following activities, in addition to drawing on our experience supporting strategic learning and evaluation in complex environments. Appendix A includes a complete list of grants reviewed and interviewees.Grants analysis: FSG analyzed Omidyar Network's Initiative Results Architecture frameworks and 23 grants within its ecosystem investment portfolio. These docu­ments helped ground our research in an understanding of the different types of ecosystem investments Omidyar Network is making, as well as how the organiza­tion currently evaluates the impact of its ecosystem investments.Literature review: FSG reviewed more than 60 publications to identify best practices in evaluating ecosystem investments—these publications included both peer-reviewed journal articles and "grey literature" (conference presentations, blog posts) by organizations employing advocacy-type strategies.Interviews: FSG conducted interviews with nine external experts (listed in Appen­dix A) to more deeply understand effective practices in evaluating the effects of eco­system investments and to identify leading organizations in this area. Interviewees were identified to glean best practices from both within and outside the traditional social sector

Designing an information system for updating land records in Bangladesh: action design ethnographic research (ADER)

Open Access. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.This article has been made available through the Brunel Open Access Publishing Fund.Information Systems (IS) has developed through adapting, generating and applying diverse methodologies, methods, and techniques from reference disciplines. Further, Action Design Research (ADR) has recently developed as a broad research method that focuses on designing and redesigning IT and IS in organizational contexts. This paper reflects on applying ADR in a complex organizational context in a developing country. It shows that ADR requires additional lens for designing IS in such a complex organizational context. Through conducting ADR, it is seen that an ethnographic framework has potential complementarities for understanding complex contexts thereby enhancing the ADR processes. This paper argues that conducting ADR with an ethnographic approach enhances design of IS and organizational contexts. Finally, this paper aims presents a broader methodological framework, Action Design Ethnographic Research (ADER), for designing artefacts as well as IS. This is illustrated through the case of a land records updating service in Bangladesh

Different perceptions of adaptation to climate change: a mental model approach applied to the evidence from expert interviews

We argue that differences in the perception and governance of adaptation to climate change and extreme weather events are related to sets of beliefs and concepts through which people understand the environment and which are used to solve the problems they face (mental models). Using data gathered in 31 in-depth interviews with adaptation experts in Europe, we identify five basic stakeholder groups whose divergent aims and logic can be related to different mental models they use: advocacy groups, administration, politicians, researchers, and media and the public. Each of these groups uses specific interpretations of climate change and specifies how to deal with climate change impacts. We suggest that a deeper understanding and follow-up of the identified mental models might be useful for the design of any stakeholder involvement in future climate impact research processes. It might also foster consensus building about adequate adaptation measures against climate threats in a society