• Digital Humanities and Cultural Heritage
• 2013-2022close
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• Scholarship@Western close

In hopes of sparking a discussion, I argue for much needed research on automated deception detection in Asian languages. The task of discerning truthful texts from deceptive ones is challenging, but a logical sequel to opinion mining. I suggest that applied computational linguists pursue broader interdisciplinary research on cultural differences and pragmatic use of language in Asian cultures, before turning to detection methods based on a primarily Western (English-centric) worldview. Deception is fundamentally human, but how do various cultures interpret and judge deceptive behavior?

Twenty-one seniors (aged 60+) were interviewedabout their use of digital technology. Grounded theoryand Key Point analysis were used to identify severalareas where these tools have become embedded intothe lives of seniors. These include informationseeking, news media, library usage, and readingpreferences.Vingt et un aînés (âgés de 60 ans et plus) ont étéinterrogés sur leur utilisation des technologiesnumériques. Nous avons utilisé la théorie ancréedans les données empiriques et l’analyse de point clépour identifier plusieurs domaines dans lesquels cesoutils se sont intégrés dans la vie des aînés. Ceux-cicomprennent la recherche d’information, lesnouvelles, l’utilisation de la bibliothèque et lespréférences de lecture.

This paper argues that big data can possess different characteristics, which affect its quality. Depending on its origin, data processing technologies, and methodologies used for data collection and scientific discoveries, big data can have biases, ambiguities, and inaccuracies which need to be identified and accounted for to reduce inference errors and improve the accuracy of generated insights. Big data veracity is now being recognized as a necessary property for its utilization, complementing the three previously established quality dimensions (volume, variety, and velocity), But there has been little discussion of the concept of veracity thus far. This paper provides a roadmap for theoretical and empirical definitions of veracity along with its practical implications. We explore veracity across three main dimensions: 1) objectivity/subjectivity, 2) truthfulness/deception, 3) credibility/implausibility – and propose to operationalize each of these dimensions with either existing computational tools or potential ones, relevant particularly to textual data analytics. We combine the measures of veracity dimensions into one composite index – the big data veracity index. This newly developed veracity index provides a useful way of assessing systematic variations in big data quality across datasets with textual information. The paper contributes to the big data research by categorizing the range of existing tools to measure the suggested dimensions, and to Library and Information Science (LIS) by proposing to account for heterogeneity of diverse big data, and to identify information quality dimensions important for each big data type.

Twenty academic historians in Southern Ontario were interviewed about their use of e-books and the role of serendipity in their research. Our findings show that serendipity continues to occur in physical environments, most often the stacks. By contrast, digital tools and texts is limiting historians’ opportunity for a chance encounter with information. Vingt historiens universitaires du sud de l'Ontario ont été interrogés sur leur utilisation des livres électroniques et sur le rôle de la sérendipité dans leurs recherches. Un thème central qui a fait surface suite à l'analyse selon la théorie ancrée dans des données empiriques est que leur utilisation des outils et des textes numériques limite leur possibilité d'une rencontre fortuite avec de l'information.

Abstract: This study analyses 545 sample fanfiction stories (fics) in their stylistic feature variation by popularity and across eleven ‘fandoms’ in creative writing forums. Lexical richness, average sentence and paragraph lengths are isolated as promising measures for a text classifier to use in predicting a fic’s likely popularity in its fandom. Résumé: Cette étude analyse un échantillon de 545 chapitres d‘œuvres de fanfiction (fics) selon leur variation stylistique et leur popularité dans onze ‘fandoms’ différents. La richesse lexicale, longueur moyenne de phrase et longueur moyenne de paragraphe ont été choisis comme traits stylistiques propres à différencier les fics populaires des fics impopulaires.