Library and Information Science Commons^™

Professional Identity And You: Why Self-Concept Matters In Librarianship, Kevin Tanner

FIMS Presentations

Kevin Tanner addresses the importance of professional identity in librarianship. In the Summer 2015 semester, he completed an independent study on the construction of professional identity of librarians on Twitter through professional development and networking. During this session, he shares the results of that study and give suggestions on how you can begin to find your own professional identity while still retaining your individuality. While there are many stereotypes about librarians, they are not “one-size-fits-all” professionals, and a new modern image of the professional has begun to emerge in the digital age through a thoughtful reflection on identity.

Awareness And Perception Of Copyright Among Teaching Faculty At Canadian Universities, Lisa Di Valentino

FIMS Presentations

In this talk I discuss the results of a survey of Canadian university faculty members undertaken from October to December 2014. The survey sought to determine teaching faculty awareness of copyright law and institutional policy and training, and how they would respond in various scenarios.

Analysis of the results suggests that while faculty members are aware of the existence of their institution's copyright policy, much fewer know whether their institution offers training. Of those who do know about training, only one-third have attended. However, faculty who have attended copyright training find that their knowledge is enhanced by the experience.

It …

Towards News Verification: Deception Detection Methods For News Discourse, Yimin Chen, Victoria L. Rubin, Niall Conroy

FIMS Presentations

News verification is a process of determining whether a particular news report is truthful or deceptive. Deliberately deceptive (fabricated) news creates false conclusions in the readers’ minds. Truthful (authentic) news matches the writer’s knowledge. How do you tell the difference between the two in an automated way? To investigate this question, we analyzed rhetorical structures, discourse constituent parts and their coherence relations in deceptive and truthful news sample from NPR’s “Bluff the Listener”. Subsequently, we applied a vector space model to cluster the news by discourse feature similarity, achieving 63% accuracy. Our predictive model is not significantly better than chance …