This paper presents a new corpus-driven approach applicable to the study of language patterns in social and political contexts, or Critical Discourse Analysis (CDA) using Distributional Semantic Models (DSMs). This approach considers changes in word semantics, both over time and between communities with differing viewpoints. The geometrical spaces constructed by DSMs or "word spaces" offer an objective, robust exploratory analysis tool for revealing novel patterns and similarities between communities, as well as highlighting when these changes occur. To quantify differences between word spaces built on different time periods and from different communities, we analyze the nearest neighboring words in the DSM, a process we relate to analyzing "concordance lines". This makes the approach intuitive and interpretable to practitioners. We demonstrate the usefulness of the approach with two case studies, following groups with opposing political ideologies in the Scottish Independence Referendum, and the US Midterm Elections 2014.
With increased adoption of social networking tools, it is becoming more difficult to extract useful information from the mass of data generated daily by users. Curation of content and sources is an important filter in separating the signal from noise. A good set of credible sources often requires painstaking manual curation, which often yields incomplete coverage of a topic. In this demo, we present a recommender system to aid this process, improving the quality and quantity of sources. The system is highly-adaptable to the goals of the curator, enabling some novel uses for curating and monitoring lists of users.
Newsletters have (re-) emerged as a powerful tool for publishers to engage with their readers directly and more eectively. Despite the diversity in their audiences, publishers' newsletters remain largely a one-size-ts-all oering, which is suboptimal. In this paper, we present NU:BRIEF, a web application for publishers that enables them to personalize their newsletters without harvesting personal data. Personalized newsletters build a habit and become a great conversion tool for publishers, providing an alternative readersgenerated revenue model to a declining ad/clickbait-centered business model.
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