Changes

One of the chief promises of linked data for libraries is search engine visibility. Few studies, however, have attempted a quantitative analysis of linked data's impact on search engine rankings. Sophisticated tools have been developed to test search visibility in the related field of search engine optimization, including rank trackers, link analyzers, site auditors, and web crawlers. The author studied a linked data project from a search engine optimization perspective, applying these tools to quantify the impact of linked data and to identify best practices for implementation.

Poster PDF: https://osf.io/wx74v/ This poster reflects an ongoing project to study the nature of the “digital librarian.” In this poster, we analyze 2017 postings from Code4Lib’s job board with job titles that include the words “digital” and “librarian” in any combination. We use NVivo and text-mining tools to look for patterns (or lack thereof) in the responsibilities, skills, and educational requirements for these positions. This work is a timely update on the evolving nature of digital librarians, and it offers a fresh and well-needed scholarly perspective on larger changes to library employment practices. As a former archaeologist and a former actress, we now find ourselves working as Digital Learning and Scholarship Librarians. A growing number of individuals are, likewise, following similarly non-traditional pathways to the library, and rightly so. The job market for new graduates across fields is perilous and many of the digital needs of libraries are going unmet. A deeper understanding of the prevailing skills that one must cultivate to become employable as a digital librarian is needed.

Slides to PDF: https://osf.io/rcq5j/ Based on the widely circulated blog post "Where to get Twitter data for academic research" (https://gwu-libraries.github.io/sfm-ui/posts/2017-09-14-twitter-data), this poster will discuss various approaches for acquiring Twitter datasets for academic research. These approaches will include collecting yourself, locating and reusing an existing dataset, purchasing a dataset, or using a Twitter service provider. In addition, the poster will highlight some of the key tools and services in acquiring Twitter datasets such as Twarc, Social Feed Manager, TweetSets, Gnip, and DiscoverText.