Untangling a Web of Lies: Exploring Automated Detection of Deception in Computer-Mediated Communication

Safeguarding organizations against opportunism and severe deception in computer-mediated communication (CMC) presents a major challenge to CIOs and IT managers. New insights into linguistic cues of deception derive from the speech acts innate to CMC. Applying automated text analysis to archival email exchanges in a CMC system as part of a reward program, we assess the ability of word use (micro-level), message development (macro-level), and intertextual exchange cues (meta-level) to detect severe deception by business partners. We empirically assess the predictive ability of our framework using an ordinal multilevel regression model. Results indicate that deceivers minimize the use of referencing and self-deprecation but include more superfluous descriptions and flattery. Deceitful channel partners also over structure their arguments and rapidly mimic the linguistic style of the account manager across dyadic e-mail exchanges. Thanks to its diagnostic value, the proposed framework can support firms’ decision-making and guide compliance monitoring system development.

The Potential of Participedia as a Crowdsourcing Tool for Comparative Analysis of Democratic Innovations

For two reasons, our capacity for systematic comparison of innovative participatory democratic processes remains limited. First, the category of participatory democratic innovations remains relatively vague when compared to more traditional democratic institutions and practices. Second, until recently there existed no large-sample databases that captured relevant variables in the practice of democratic innovation. The lone exception to these patterns is the Participedia database, located online. Participedia is well placed to respond to the two obstacles to systematic comparative research on democratic innovation. First, its crowdsourced data collection strategy means that many of the cases on the platform are not well known and have not been the subject of sustained academic analysis. Second, the data captured in the articles provides the basis for systematic comparative analysis of democratic innovations both within type (e.g., participatory budgeting, mini-publics) and across types. The platform allows for systematic content analysis of text descriptions and/or statistical analysis of the datasets generated from the structured data fields. This article describes the data about innovative participatory democratic processes available from Participedia, and furnishes examples of the kinds of quantitative and qualitative insights about those processes that Participedia enables.

Technical Vocabulary and Medieval Text Types: A Semantic Field Approach

This paper seeks to discover in what sense we can classify vocabulary items as technical terms in the later medieval period. In order to arrive at a principled categorization of technicality, distribution is taken as a diagnostic factor: vocabulary shared across the widest range of text types may be assumed to be both prototypical for the semantic field, but also the most general and therefore least technical terms since lexical items derive at least part of their meaning from context, a wider range of contexts implying a wider range of senses. A further way of addressing the question of technicality is tested through the classification of the lexis into semantic hierarchies: in the terms of componential analysis, having more components of meaning puts a term lower in the semantic hierarchy and flags it as having a greater specificity of sense, and thus as more technical. The various text types are interrogated through comparison of the number of levels in their hierarchies and number of lexical items at each level within the hierarchies. Focusing on the vocabulary of a single semantic field, DRESS AND TEXTILES, this paper investigates how four medieval text types (wills, sumptuary laws, petitions, and romances) employ technical terminology in the establishment of the conventions of their genres.