Alle Publikationen
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2019
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(2019): Understanding Legal Meaning through Word Embeddings. In: SSRN Electronic Journal. DOI: 10.2139/ssrn.3455747
DOI: https://doi.org/10.2139/ssrn.3455747 Abstract: For judges and legal scholars, the quest for meaning and the identification of methods appropriate for understanding word meaning animates volumes upon volumes of debate. Likewise, social scientists interested in studying the law have increasingly recognized the variations in choices over words as important barometers for understanding the law. In this paper, I suggest recent advances in computational linguistics -- notably, the efficient estimation of distributed representations of word meanings, or word embeddings -- offer a potentially transformative avenue by which to assess the strategy, choice, and impact of judicial language. Utilizing a corpus of more than one million federal and state appellate court decisions, I estimate word embeddings for the more than 400,000 most common words found in legal opinions. In a series of simple illustrations, I demonstrate the value of this treatment of word meaning for new avenues of law and politics research.
2017
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(2017): Stereotype negation in Frame Semantics. In: Glossa: a journal of general linguistics 2 (1). DOI: 10.5334/gjgl.293Keywords: affixation, contextual coercion, frame semantics, Framesemantik, Frame-Semantik, Intellektualtechnik, Kogn. Architektur, Kontext, lexical negation, lexical rules, Lexik, Linguistik, Mensch-Technik-Relationen (MTR), Negation, Observablen/Kriterien für sozial angemessenes Verhalten und dessen Bewertung, Sprachgebrauch, Sprachverstehen, Status / biologische Marker, Technik
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(2017): How can the study of action kinematics inform our understanding of human social interaction?. In: Neuropsychologia 105, S. 101-110. DOI: 10.1016/j.neuropsychologia.2017.01.018
DOI: http://www.ncbi.nlm.nih.gov/pubmed/28119002 Abstract: The kinematics of human actions are influenced by the social context in which they are performed. Motion-capture technology has allowed researchers to build up a detailed and complex picture of how action kinematics vary across different social contexts. Here we review three task domains-point-to-point imitation tasks, motor interference tasks and reach-to-grasp tasks-to critically evaluate how these tasks can inform our understanding of social interactions. First, we consider how actions within these task domains are performed in a non-social context, before highlighting how a plethora of social cues can perturb the baseline kinematics. We show that there is considerable overlap in the findings from these different tasks domains but also highlight the inconsistencies in the literature and the possible reasons for this. Specifically, we draw attention to the pitfalls of dealing with rich, kinematic data. As a way to avoid these pitfalls, we call for greater standardisation and clarity in the reporting of kinematic measures and suggest the field would benefit from a move towards more naturalistic tasks.
Keywords: Favoriten, Imitation, Interaktion, interference of social interaction, Kinematics, kinematics and social interaction, Kinematik, kinematische Dimension, Kontext, Körperbewegungen / Kinematik, Modelle/Theorien, Motor, Observablen/Kriterien für sozial angemessenes Verhalten und dessen Bewertung, social, social interaction, Soziale Angemessenheit 2015
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(2015): Implicit Contextual Integrity in Online Social Networks. In: Information Sciences 325, S. 48-69. DOI: 10.1016/j.ins.2015.07.013
Abstract: Many real incidents demonstrate that users of Online Social Networks need mechanisms that help them manage their interactions by increasing the awareness of the different contexts that coexist in Online Social Networks and preventing them from exchanging inappropriate information in those contexts or disseminating sensitive information from some contexts to others. Contextual integrity is a privacy theory that conceptualises the appropriateness of information sharing based on the contexts in which this information is to be shared. Computational models of Contextual Integrity assume the existence of well-defined contexts, in which individuals enact pre-defined roles and information sharing is governed by an explicit set of norms. However, contexts in Online Social Networks are known to be implicit, unknown a priori and ever changing; users relationships are constantly evolving; and the information sharing norms are implicit. This makes current Contextual Integrity models not suitable for Online Social Networks. In this paper, we propose the first computational model of Implicit Contextual Integrity, presenting an information model for Implicit Contextual Integrity as well as a so-called Information Assistant Agent that uses the information model to learn implicit contexts, relationships and the information sharing norms in order to help users avoid inappropriate information exchanges and undesired information disseminations. Through an experimental evaluation, we validate the properties of the model proposed. In particular, Information Assistant Agents are shown to: (i) infer the information sharing norms even if a small proportion of the users follow the norms and in presence of malicious users; (ii) help reduce the exchange of inappropriate information and the dissemination of sensitive information with only a partial view of the system and the information received and sent by their users; and (iii) minimise the burden to the users in terms of raising unnecessary alerts. (C) 2015 Elsevier Inc. All rights reserved.
Keywords: computational model, contextual integrity, Contextual Integrity Theory, Daten, Datenschutz, Datenschutz & Privatssphäre, Disziplin, doppelter Treffer, Ethik, Favoriten, Im (wissenschaftlichen) Diskurs, incident of social interaction, Informations- & Kommunikationstechnik, Kontext, Medienwissenschaft, Mensch-Technik-Relationen (MTR), Modelle/Theorien, Philosophie, Privacy and data, privacy theorie, Realtechnik, Reflexionen über MTR, Soziale Angemessenheit, Soziale Netzwerke, Technik, Technikphilosophie
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