Disambiguierung deutschsprachiger Diskursmarker: Eine Pilot-Studie

Discourse markers such as German aber, wohl or obwohl can be regarded as valuable information for a wide range of text-linguistic applications, since they provide important cues for the interpretation of texts or text segments. Unfortunately, many of them are highly ambiguous. Thus, for their use in applications like automatic text summarizations a reliable disambiguation of discourse markers is needed. This should be done automatically, since manual disambiguation is feasible only for small amounts of data. The aim of this pilot study, therefore, was to investigate methodological requirements of automatic disambiguation of German discourse markers. Two different methods known from word-sense disambiguation, Naive-Bayes and decisionlists, were used for the highly ambiguous marker wenn. A statistical approach was taken to compare the two approaches and different feature combinations

Citizen Perspectives on Necessary Safeguards to the Use of AI by Law Enforcement Agencies

In the light of modern technological advances, Artificial Intelligence (AI) is relied upon to enhance performance, increase efficiency, and maximize gains. For Law Enforcement Agencies (LEAs), it can prove valuable in optimizing evidence analysis and establishing proactive prevention measures. Nevertheless, citizens raise legitimate concerns around privacy invasions, biases, inequalities, and inaccurate decisions. This study explores the views of 111 citizens towards AI use by police through interviews, and integrates societal concerns along with propositions of safeguards from negative effects of AI use by LEAs in the context of cybercrime and terrorism.Comment: CSCE 2022 Conference Proceeding

What do citizens communicate about during crises? Analyzing twitter use during the 2011 UK riots

Abstract The use of social media during crises has been explored in a variety of natural and man-made crisis situations. Yet, most of these studies have focused exclusively on the communication strategies and messages sent by crisis responders. Surprisingly little research has been done on how crisis publics (i.e., those people interested in or affected by the crisis) use social media during such events. Our article addresses this gap in the context of citizens' Twitter use during the 2011 riots in the UK. Focusing on communications with and about police forces in two cities, we analyzed 5984 citizen tweets collected during the event for content and sentiment. Comparing the two cases, our findings suggest that citizens' Twitter communication follows a general logic of concerns, but can also be influenced very easily by single, non-crisis related events such as perceived missteps in a police force's Twitter communication. Our study provides insights into citizens' concerns and communication patterns during crises adding to our knowledge about the dynamics of citizens' use of social media in such times. It further highlights the fragmentation in Twitter audiences especially in later stages of the crisis. These observations can be utilized by police forces to help determine the appropriate organizational responses that facilitate coping across various stages of crisis events. In addition, they illustrate limitations in current theoretical understandings of crisis response strategies, adding the requirement for adaptivity, flexibility and ambiguity in organizational responses to address the observed plurivocality of crisis audiences

What Determines Inter-Coder Agreement in Manual Annotations? A Meta-Analytic Investigation

Recent discussions of annotator agreement have mostly centered around its calculation and interpretation, and the correct choice of indices. Although these discussions are important, they only consider the "back-end" of the story, namely, what to do once the data are collected. Just as important in our opinion is to know how agreement is reached in the first place and what factors influence coder agreement as part of the annotation process or setting, as this knowledge can provide concrete guidelines for the planning and set-up of annotation projects. To investigate whether there are factors that consistently impact annotator agreement we conducted a meta-analytic investigation of annotation studies reporting agreement percentages. Our meta-analysis synthesized factors reported in 96 annotation studies from three domains (word-sense disambiguation, prosodic transcriptions, and phonetic transcriptions) and was based on a total of 346 agreement indices. Our analysis identified seven factors that influence reported agreement values: annotation domain, number of categories in a coding scheme, number of annotators in a project, whether annotators received training, the intensity of annotator training, the annotation purpose, and the method used for the calculation of percentage agreements. Based on our results we develop practical recommendations for the assessment, interpretation, calculation, and reporting of coder agreement. We also briefly discuss theoretical implications for the concept of annotation quality

Citizen repertoires of smart urban safety: Perspectives from Rotterdam, the Netherlands

This article provides empirical research about the perspectives of citizens of Rotterdam, the Netherlands, on the emergent phenomenon of ‘smart urban safety’, which advocates advanced uses of digital technologies and data for urban safety management, and is gaining currency in thinking about urban futures. While smart cities affect many dimensions of city management, applications to safety management belong to the most controversial, revealing important tensions between disparate perspectives on technology and society in the context of urban living environments. Despite their influence, the concepts of smart cities and smart urban safety are largely unknown to the public. To gain insights into citizens’ perspectives, this study uses smart urban safety vignettes to which participants are invited to respond. Using discourse analytical techniques, their interpretations of safety in the smart city are described, which center on functional designs, express lacking influence over technological developments, and reflect on benefits and risks and on their civic roles vis-à-vis technologically mediated urban safety management. Our article concludes by arguing how these findings complement, but also show limitations to traditional technology acceptance models that are as of yet dominant in research of smart urban safety specifically, and smart cities more generally

The digital mediation of migration: a qualitative thematic synthesis

The highly complex economic, political, social and cultural processes of migration are increasingly digitally mediated. A rich area of research examining this phenomenon is emerging at the confluence of information and communication technology (ICT) and social sciences. However, little has been done to systematically review this literature. Through a qualitative thematic synthesis (QTS), this paper presents a fusion of recent research to identify: 1) what technologies are being used by migrants to the EU and how and 2) what are the impacts of technology on migrants and migration processes. By bridging the findings of multidisciplinary works, this QTS demonstrates how digital media and technology affect migrant experiences in both positive and negative ways as well as evidence of their impact on migratory trends. It highlights key gaps in the literature and suggests further areas for intervention, identifying the need for a cross-disciplinary research agenda that addresses causal relationships between effects of technology and migration processes

Surveillance and falsification implications for open source intelligence investigations

© 2015 ACM. Legitimacy of surveillance is crucial to safeguarding validity of OSINT data as a tool for law-enforcement agencies

Conditions, Actions and Purposes (CAP): A Dynamic Model for Community Policing in Europe

Despite its popularity as a policing method and evidence of its positive affect on communities, community policing has defied attempts to establish a clear definition and replicable form. Often regarded as an Anglo-American policing method in origin, community policing is now found across the world and is growing in influence. The need for differentiated local implementation raises important questions regarding the core features of community policing to guide the work of practitioners. Integrating insights from the existing literature and a trans-European project involving 323 interviews with community members and police officers across eight countries, we propose a dynamic model for community policing. In this original model, we differentiate between the conditions, actions and purposes of community policing (CAP) and describe how these core components are required for effective community policing, interrelated, and flexible enough for local implementation. Accordingly, we show how the CAP model is adaptable while at the same time retaining a sense of what makes ‘community policing’ a unique and identifiable policing method. We conclude our study with a discussion of the implications for research and practice internationally

Revenge by photoshop: Memefying police acts in the public dialogue about injustice

In this article, we are interested in the role digital memes in the form of pictures play in the framing of public discourses about police injustice and what it is that makes memes successful in this process. For this purpose, we narrate the story of one such meme: the ‘pepper-spray cop’. In our analysis, we link the creation and spread of the meme to the democratization of online activism and the subversive acts of hierarchical sousveillance. Based on our findings, we discuss features of the meme and the process linked to its initiation, rapid spread and disappearance as vital for the success of visual memes in the context of online protests

Text type structure and logical document structure

Most research on automated categorization of documents has concentrated on the assignment of one or many categories to a whole text. However, new applications, e.g. in the area of the Semantic Web, require a richer and more fine-grained annotation of documents, such as detailed thematic information about the parts of a document. Hence we investigate the automatic categorization of text segments of scientific articles with XML markup into 16 topic types from a text type structure schema. A corpus of 47 linguistic articles was provided with XML markup on different annotation layers representing text type structure, logical document structure, and grammatical categories. Six different feature extraction strategies were applied to this corpus and combined in various parametrizations in different classifiers. The aim was to explore the contribution of each type of information, in particular the logical structure features, to the classification accuracy. The results suggest that some of the topic types of our hierarchy are successfully learnable, while the features from the logical structure layer had no particular impact on the results