leanEA. A poor man\u27s evolving algebra compiler

The Prolog program term_expansion((define C as A with B), (C=>A:-B,!)). term_expansion((transition E if C then D), ((transition E):-C,!,B,A,(transition _))) :- serialize(D,B,A). serialize((E,F),(C,D),(A,B)) :- serialize(E,C,B), serialize(F,D,A). serialize(F:=G, ([G]=>*[E],F=..[

Implementing semantic tableaux

This report describes implementions of the tableau calculus for first-order logic. First an extremely simple implementation, called leanTAP, is presented, which nonetheless covers the full functionality of the calculus and is also competitive with respect to performance. A second approach uses compilation techniques for proof search. Improvements inculding universal variables and lemmata are considered as well as more efficient data structures using reduced ordered binary decision diagrams. The implementation language is PROLOG. In all cases fully operational PROLOG code is given. For leanTAP a formal proof of the correctness of the implementation is given relying on the operational semantics of PROLOG as given by the SLD-tree model. This report will appear as a chapter in the Handbook of Tableau-based Methods in Automated Deduction edited by: D. Gabbay, M. D\u27Agostino, R. H\"{a}hnle, and J.Posegga published by: KLUWER ACADEMIC PUBLISHERS Electronic availability will be discontinued after final acceptance for publication is obtained

Characterizing Political Talk on Twitter: A Comparison Between Public Agenda, Media Agendas, and the Twitter Agenda with Regard to Topics and Dynamics

Social media platforms, especially Twitter, have become a ubiquitous element in political campaigns. Although politicians, journalists, and the public increasingly take to the service, we know little about the determinants and dynamics of political talk on Twitter. We examine Twitter’s issue agenda based on popular hashtags used in messages referring to politics. We compare this Twitter agenda with the public agenda measured by a representative survey and the agendas of newspapers and television news programs captured by content analysis. We show that the Twitter agenda had little, if any, relationship with the public agenda. Political talk on Twitter was somewhat stronger connected with mass media coverage, albeit following channel-specific patterns most likely determined by the attention, interests, and motivations of Twitter users

Evaluating a mobile crisis response system for the management of disaster volunteers

As part of an ongoing research project, we have designed and implemented a mobile crisis response system (MCRS), which creates a nexus between relief organizations and unaffiliated disaster volunteers. We developed the MCRS using a design science approach and address information management, coordination, and motivation challenges in the context of managing unaffiliated disaster volunteers in crisis response and disaster relief activities. In this researchin- progress paper, we propose a design for the evaluation of the MCRS prototype based on a field experiment, which will be conducted during a joint mission exercise performed by three major German relief organizations. We adapt the enterprise systems success model and suggest evaluating the system quality, information quality, individual impact, and organizational impact of the prototype

What Do They Meme? Exploring the Role of Memes as Cultural Symbols of Online Communities

Analyzing symbols shared within online communities (OCs) is essential to better understand communities’ expressed cultures. To evaluate how OCs differ in their expressed culture and analyze the effects of community rules (CR) and moderation policies (MP), we examined meme sharing of subreddit and interaction communities on Reddit. To detect memes shared within subreddits automatically, we trained a convolutional neural network and applied a feature-matching algorithm to create meme networks with components consisting of visually similar memes. Based on each community’s component composition, we created community-specific meme languages that we compared across subreddit and interaction communities. Our results show that memes can be aggregated to characteristic meme languages linked to individual OCs; yet MP and CR do not impact the homogeneity of shared memes. Based on these findings, we plan to analyze dynamically the relationship between memes and OCs, examining memes’ textual content and diving deeper into users’ individual meme languages

Establishing Information Quality Guidelines in Social Information Systems: Comparison and Discussion of Two Approaches

Social Information Systems (SocIS) enable many people to interact digitally and collaboratively create and share digital content. Nevertheless, the large and heterogenous SocIS communities make it challenging to ensure information quality (IQ) because members’ interpretation and evaluation of content might be very different. As a remedy, many platforms explicitly state normative IQ guidelines. Guidelines can be developed either by the community members themselves or by the platform provider (and imposed on the community). It is unclear, however, which of these two approaches members agree with more strongly and which produces the more satisficatory IQ guidelines. Through an empirical survey study covering 15 different SocIS platforms, we find that members do agree more and are more satisfied when guidelines have been developed by the community. These findings are important for platform providers to improve IQ and retain members, and also inform research on IQ in SocIS

Decision Making in Emergency Management: The Role of Social Media

Researchers and practitioners alike recognise the importance of emergency management (EM) in limiting the adverse impacts of crisis events, as well as the promise of social media to support these efforts. Decision making, which is crucial to ensure the effective management of immediate, emerging, and sustained crises, is one facet of EM potentially affected by social media. While much research has investigated social media in a crisis context more generally, little is known thus far about what it means for EM decision making. In this paper, we investigate the current knowledge base of this phenomenon and infer from it factors that are crucial for its understanding. To this end, we propose an analytical framework of EM decision making based on previous work on complex problem solving and social media networks. We then systematically review and rethink existing research from a decision-centred point of view to identify and synthesise key findings that are relevant to the role of social media in the EM decision-making process. Finally, we outline the research gaps that need to be closed to arrive at a more comprehensive understanding of social media for EM decision support and to begin moving towards theoretically grounded explanations of the phenomenon

Collective Dynamics of Digitally Enabled Social Networks

This thesis investigates the role of technology in the collective dynamics of digitally enabled social networks. Based on a review of the historical foundation of research on crowds, collective behaviour, and collective dynamics in the social sciences and in research on complex systems, it develops a conceptualisation of collective dynamics in the context of digitally enabled social networks. This conceptualisation provides the foundation for one overarching and three subordinate research questions dedicated to different aspects of the role technology plays in understanding and managing the collective dynamics of digitally enabled social networks. The body of work comprising this dissertation is distributed across fifteen papers that contribute to these research questions

How Human-AI Collaboration Affects Attribution of Responsibility for Failure and Success

Individuals increasingly seek algorithmic advice to optimize their decision making. This study aims to investigate the effects of receiving algorithmic advice on individuals’ attribution of responsibility for their achievements. The study is based on an experiment with a 2 x 5 design of two dimensions: achievement (success vs. failure) and advice (no advice; human-based advice with high and low expertise; and algorithmic advice with high and low accuracy). The findings from a pilot study suggest that the experimental design is largely appropriate, given that we found answers to our hypotheses. This short paper provides valuable insights for future research on the attribution of responsibility for success and failure when receiving algorithmic advice