Historical case study: A research strategy for diachronic analysis

History and case study are two diachronic research strategies commonly used to study political discourse as it relates to public libraries. Though suitable for some studies, these strategies are inexhaustive. A new, blended research strategy is therefore needed to accomplish what history and case study alone cannot. This hybrid strategy, historical case study, must analyze cases from the distant past to the present, using eclectic data sources, in order to produce both idiographic and nomothetic knowledge. To develop historical case study, the universal components of diachronic analysis are first identified. A general research design for historical case study is then introduced. Finally, historical case study is tested in an actual research project. Findings from this project reveal that historical case study is a successful diachronic research strategy. Historical case study is a new and valuable research design suitable for addressing questions related to change, continuity, development, and evolution.     

Social Comparisons and Need Fulfillment: Interpreting Video Game Enjoyment in the Context of Leaderboards

This study examines how social comparison information provided by video game leaderboards may influence players’ retrospective judgments of autonomy, competence, and relatedness need fulfillment. Participants played a video game and were randomly assigned to receive no postgame feedback or were shown a leaderboard that placed them in the top or bottom quartile of players. Results indicate downward social comparisons increase enjoyment by increasing competence and relatedness perceptions. However, upward comparisons did not have an opposite effect, nor did either type of social comparison influence players’ autonomy perceptions. Implications for applying Self-Determination Theory to video game enjoyment in the context of social comparison feedback is discussed.     

Persistent Misperceptions: Americans’ Misplaced Confidence in Privacy Policies, 2003–2015

This paper examines the persistence of Americans’ misunderstanding of the function of privacy policies. We also identify groups that have misplaced confidence in the privacy policy label and address whether the groups’ patterns of misperception have changed over time. The findings add a new dimension to the argument that the usefulness of privacy policies needs to be reassessed. As a remedy, we call for media literacy programs to address structural features of media systems that lead to broadly held misperceptions such as the one examined here.     

Bringing the Law to the Library: The Importance of Librarian Mediation in Access to Justice Services

Library access to justice programs and services help people who need legal information and who cannot afford an attorney. Librarian mediation is a critical component in the provision of access to justice services. However, the value of library mediation, or assistance with using library resources, is often unrecognized, particularly where members of the public are trying to access electronic legal information sources, online legal forms, and other law technologies. This article will explore the role of librarians in providing access to justice services from the perspective of the work of Richard Susskind, which emphasizes technological approaches to providing legal services. While there is a place for technology in access to justice services, there is also a valuable role that librarians play in contributing to access to justice.     

Retrieving and classifying instances of source code plagiarism

Automatic detection of source code plagiarism is an important research field for both the commercial software industry and within the research community. Existing methods of plagiarism detection primarily involve exhaustive pairwise document comparison, which does not scale well for large software collections. To achieve scalability, we approach the problem from an information retrieval (IR) perspective. We retrieve a ranked list of candidate documents in response to a pseudo-query representation constructed from each source code document in the collection. The challenge in source code document retrieval is that the standard bag-of-words (BoW) representation model for such documents is likely to result in many false positives being retrieved, because of the use of identical programming language specific constructs and keywords. To address this problem, we make use of an abstract syntax tree (AST) representation of the source code documents. While the IR approach is efficient, it is essentially unsupervised in nature. To further improve its effectiveness, we apply a supervised classifier (pre-trained with features extracted from sample plagiarized source code pairs) on the top ranked retrieved documents. We report experiments on the SOCO-2014 dataset comprising 12K Java source files with almost 1M lines of code. Our experiments confirm that the AST based approach produces significantly better retrieval effectiveness than a standard BoW representation, i.e., the AST based approach is able to identify a higher number of plagiarized source code documents at top ranks in response to a query source code document. The supervised classifier, trained on features extracted from sample plagiarized source code pairs, is shown to effectively filter and thus further improve the ranked list of retrieved candidate plagiarized documents.     

More than Bags of Words: Sentiment Analysis with Word Embeddings

ABSTRACT

Moving beyond the dominant bag-of-words approach to sentiment analysis we introduce an alternative procedure based on distributed word embeddings. The strength of word embeddings is the ability to capture similarities in word meaning. We use word embeddings as part of a supervised machine learning procedure which estimates levels of negativity in parliamentary speeches. The procedure’s accuracy is evaluated with crowdcoded training sentences; its external validity through a study of patterns of negativity in Austrian parliamentary speeches. The results show the potential of the word embeddings approach for sentiment analysis in the social sciences.     

Expanding opportunities to learn to support inclusive education through drama‐enhanced literacy practices

This study examines how the Early Years Educators at Play (EYEPlay) professional development (PD) programme supported inclusive learning settings for all children, including English language learners and students with disabilities. The EYEPlay PD model is a year‐long programme that integrates drama strategies into literacy practices within real‐classroom contexts. Inclusive education refers to ensuring equal opportunities to access and participation in learning activities for all students. Cultural‐historical activity theory was used to understand and unpack the drama practices. Twelve semi‐structured focus group interviews were conducted with 19 preschool teachers. The data were analysed via constant‐comparative and interpretive methods. The study findings showed that EYEPlay PD practices enhanced inclusive learning settings for diverse groups of students by increasing access and expanding opportunities to learn, and supporting a positive learning environment.