Text Analysis for Knowledge Graphs

Popping, Roel

doi:10.1007/s11135-006-9020-z

Cited by 5 publications

(3 citation statements)

References 18 publications

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“…In the first step, a human coder is given a political party manifesto, which he or she then divides into discrete, nonoverlapping text units known as “quasi‐sentences.” Quasi‐sentences are textual units that express a policy proposition and may be either a complete natural sentence or part of one. Once identified, the quasi‐sentence is then assigned to one of 56 mutually exclusive policy categories, distributed across seven broad policy domains such as “Political System” or “Economy.” CMP data thus take the form of counts of sentences in categories, a unit of analysis that is intermediate between the more holistic analysis offered by an interpretative approach and more detailed syntactic analyses (Popping 2007; van Atteveldt, Kleinnijenhuis, and Ruigrok 2008) and purely lexical approaches (Laver, Benoit, and Garry 2003; Slapin and Proksch 2008). Category counts are then converted to percentages by dividing by the total number of sentences in the manifesto.…”

Section: How Should Policy Mentions Be Counted?mentioning

confidence: 99%

Scaling Policy Preferences from Coded Political Texts

Lowe

Benoit

Mikhaylov

et al. 2011

Legislative Studies Qtrly

482

477

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Scholars estimating policy positions from political texts typically code words or sentences and then build left-right policy scales based on the relative frequencies of text units coded into different categories. Here we reexamine such scales and propose a theoretically and linguistically superior alternative based on the logarithm of oddsratios. We contrast this scale with the current approach of the Comparative Manifesto Project (CMP), showing that our proposed logit scale avoids widely acknowledged flaws in previous approaches. We validate the new scale using independent expert surveys. Using existing CMP data, we show how to estimate more distinct policy dimensions, for more years, than has been possible before, and make this dataset publicly available. Finally, we draw some conclusions about the future design of coding schemes for political texts.l sq_6 123..156Almost anyone interested in party competition, whether this takes place in legislatures, the electoral arena, or government, needs sooner or later to estimate the policy positions of key political actors, whether these be individual legislators or the political parties to which they affiliate. Indeed, "how to best measure the policy preferences of individual legislators and of legislative parties" (Loewenberg 2008, 499) forms one of the central problems of legislative research. This is particularly true for scholars of comparative legislative research. While in the American settings policy preferences of legislators have been conceptualized as individual-level variables, tight party discipline in many non-American contexts makes it difficult to derive

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Section: How Should Policy Mentions Be Counted?mentioning

confidence: 99%

Scaling Policy Preferences from Coded Political Texts

Lowe

Benoit

Mikhaylov

et al. 2011

Legislative Studies Qtrly

482

477

View full text Add to dashboard Cite

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“…A citizen' s cognitive representation of a public issue can be mapped out as a seman tic network that contains both "cognitions" and "how these cognitions are connected" (Carley and Palmquist, 1992;Johnson-Laird, 2010;Morgan et al, 2001;Popping, 2006), with the nature of ties varying from general associations to specific types like perceived causal relationships. Most public opinion research is concerned with evaluative judg ments (e.g., support or oppose); mapping the full range of concepts underlying those judgments can reveal more information about individual issue positions.…”

Section: Researchmentioning

confidence: 99%

Semantic Networks and Applications in Public Opinion Research

Yang¹,

González‐Bailón²

2016

Oxford Handbooks Online

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Semantic networks represent and model messages and discourse as a relational structure, emphasizing patterns of interdependence among semantic units or actors-concepts. This chapter traces the epistemological roots of semantic networks, then illustrates with examples how this approach can contribute to the study of political rhetoric or opinions. It focuses on three levels of analysis: cognitive mapping at the individual level, discourse analysis at the interpersonal level, and framing and salience at the collective level. Drawing from the rich literature on natural language processing and machine learning, the chapter introduces readers to essential methodological considerations when extracting and building up semantic networks from textual data. It also offers a discussion on the relevance of semantic networks to analyzing public opinion, especially as it manifests in discursive and deliberative theories of democracy.

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“…As one of basic tool of text mining and information retrieval, text analysis [1,2] refers to the representation of text and the selection of its features. The primary task of text analysis is to transform an unstructured original text into structured information that can be recognized and processed by a computer.…”

Section: Introductionmentioning

confidence: 99%

TEXT Analysis on Ocean Engineering Equipment Industry Policies in China between 2010 and 2020

Ren¹,

Ge²

2022

Symmetry

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The ocean engineering equipment industry is the foundation for the implementation of maritime strategy. China’s national departments at all levels have developed relevant ocean engineering equipment industry policies to promote the rapid development of the industry. By using 56 industrial policies issued between 2010 and 2020 as the research sample, we conducted an in-depth assessment of the external structural characteristics and structure of the main cooperation network for such policies using descriptive statistics and social network analysis. Based on a symmetric analysis method, the two-dimensional matrix of cooperation breadth and cooperation depth, together with the measurement of the issuing subject’s centrality, was used to analyze the evolution of the subject’s role in the network. The research shows that the development of China’s ocean engineering equipment industry policies can be divided into three stages, and there are the following problems during the development of policies: (1) some policies and regulations are imperfect; (2) the network of cooperation among joint issuers is limited; and (3) some policies are issued by multiple government departments, but there is a lack of specialized and unified management from an absolute core department. Based on the above problems, we present some suggestions for policy optimization at the end of this paper.

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Text Analysis for Knowledge Graphs

Cited by 5 publications

References 18 publications

Scaling Policy Preferences from Coded Political Texts

Scaling Policy Preferences from Coded Political Texts

Semantic Networks and Applications in Public Opinion Research

TEXT Analysis on Ocean Engineering Equipment Industry Policies in China between 2010 and 2020

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