Editorial

This issue of the Journal contains three interesting articlesabout central aspects of public opinion research, as well asan equal number of research notes that reflect the range oftopics that interest all public opinion researchers. Toshio Takeshita takes a turn at reconceptualizing agenda-settingstudies, using a taxonomy     

Analysis of format duplication in an academic library collection

The issue of format duplication in academic library collections is increasingly complicated and perplexing in an environment of static or dwindling resources, soaring user expectations, dynamic access models, and inconsistent and changing publisher and vendor pricing structures. The problem is further complicated for libraries serving a university with multiple campus locations. This paper surveys recent investigative projects and highlights the work of a Duplicate Formats Task Force at Pennsylvania State University charged with determining the extent and nature of format duplication at that institution.     

传媒经济学研究的历史、方法与范例

本文主要回顾了传媒经济学在西方的发展历程、研究方法以及不同时期的研究议题。传媒经济学是构建于不同的经济学理论和分析方法之上的应用性学科,它致力于研究经济和金融力量如何影响传媒体系和传媒组织。西方传媒经济学创建于20世纪50年代,至今已发展成为一个活跃的和跨学科研究领域。文章认为,西方传媒经济学的主要研究范例包括理论型、应用型和批评型范例;其研究方法可分为行业市场研究、公司研究和影响力研究。在介绍西方传媒经济学研究的同时,本文还简要回顾了传媒经济学在中国的兴起与发展。     

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.     

White lies: a racial history of the (post)truth

In the aftermath of the 2016 election of President Trump, a veritable cottage industry of opinion pieces, blogs, and articles emerged overnight, most of which seemed to agree that only the post-truth could explain how a racist, misogynistic, neo-nationalist member of the economic elite could win a presidential election. This article, in contrast, is inspired by Barbara Christian’s injunction that we question why a given statement, concept, or theory is now acceptable when before it was not. Operating in this spirit, we critique post-truth critics for neglecting the material tradition of ideological criticism in favor of epistemological explanations for understanding post-truth literature; we then offer two case studies—American drug policy and housing policy—to illustrate the racial amnesia required for claiming that only now do we live in a post-truth era.