Rebellion, crime and violence in Qing China, 1722–1911: A topic modeling approach

Miller, Ian Matthew

doi:10.1016/j.poetic.2013.06.005

Cited by 36 publications

(18 citation statements)

References 3 publications

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“…We employed topic modeling to analyze and label the emergence and diffusion of topics across time and key actors (the automotive companies, the State, and the media) because this method is particularly suited to highlight patterns of meaning in a large corpus of texts and show changes in culture across time (Mohr et al 2013, p. 675;Bonilla and Grimmer 2013, Miller 2013. Topic modeling is also a great complement to network text analysis because it treats texts as "bags of words" (Giorgi and Weber 2015) that loosely co-occur within documents, and are identified in a probabilistic fashion (unlike network text analysis' more deterministic approach to meaning that highlights co-occurrences within a text).…”

Section: Qualitative Content Analysismentioning

confidence: 99%

On the Relationship Between Firms and Their Legal Environment: The Role of Cultural Consonance

Giorgi

Maoret

Zajac

2019

Organization Science

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In this study we seek to reconcile diverging dominant views on the relationship between firms and their legal environment by offering a cultural contingency perspective. We begin by accepting the notion that a new law will likely exert a powerful influence on targeted firms and that firms’ strategic responses include efforts to shape the impact of the new law. However, we suggest that the success of such response will be contingent on the degree of cultural consonance of firms’ strategic responses and the dominant cultural context at that time. We elaborate this view in our detailed qualitative and quantitative analyses of the automotive Safety Act of 1966 and the response by targeted firms. We provide evidence showing that the changes in the degree of cultural consonance of firms’ strategic response and the predominant cultural beliefs/values explain both the early failure of firms’ efforts to shape the impact of the law in the mid-1960s and the later success by the end of the 1970s. We highlight how firms’ cultural context provides both a constraint and an opportunity for firms seeking to shape legal environmental pressures, and we conclude by discussing the implications of our dynamic contingency perspective for research on law, culture, and strategy.

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Section: Qualitative Content Analysismentioning

confidence: 99%

On the Relationship Between Firms and Their Legal Environment: The Role of Cultural Consonance

Giorgi

Maoret

Zajac

2019

Organization Science

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“…Topic Modeling is a newborn in management studies, with few exceptions (Bao and Datta, 2014;Kaplan and Vakili, 2015). Nonetheless, it has been used in sociocultural studies that analyze words in order to make sense of societal issues (Miller, 2013), analyze media attention for terrorist alert (Bonilla and Grimmer, 2013) compare disciplinary evolutions (Marshall, 2013), perform humanities research in publishing studies (Tangherlini and Leonard, 2013;Jockers and Mimmo, 2013) and analyze "grammar of motives" in National Security Strategies . Varieties of procedures and issues related to topic modeling usage can be found in the admirable work by McFarland and colleagues (2013).…”

Section: Methods and Datamentioning

confidence: 99%

No Country for Neoliberalism: A Topic Modeling Approach to Protean Discourses to Resist Privatizations in Italy

Pareschi

Mollona

2016

SSRN Journal

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This paper analyzes the resistance to the neoliberal discourse supporting privatizations in the Italian sociopolitical field: we address the change from a state control over economy to a situation where most of the state owned enterprises are sold and neoliberal principles are widely adopted and accepted. We focus on resistance, which builds on two frames that differ according to the period when they arise, the words they are composed of, the meanings they bear upon. The first one, which is more prevalent in the period 1984-2000, and that we called "values of developmental state", opposes privatizations from a technical point of view: it is used in quotes that rationally support state intervention in economy. The second frame, that we called "stigma privatizations", becomes prevalent starting in 2000 and appears mainly in articles that deal with societal issues, literature, movies and the wider sociocultural debate. Here influential speakers blame privatizations as something that eroded societal cohesion. To explain the transformation, we mobilize the concept of capital as described by Bourdieu: as economic capital attached to delegitimized institutions erode, discourse on resistance does not disappear but is framed within the fields that are less dependent on economic capital. As a connected contribution, the key role played by cultural capital in preserving areas of resistances revives the debate on the role of intellectuals within 2/40 power dynamics as described by Antonio Gramsci. From a technical point of view, we study the evolution of the vocabulary of privatizations by analyzing almost 70.000 articles in the period 1984-2014. we use Topic Modeling, that is an automated text analysis technique that elicits topics, which are the sets of words that constitute discourses. We then reconstruct frames starting from these topics.

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“…Since the introduction of latent Dirichlet allocation (LDA)-the archetypical and still the widely used probabilistic topic model-in 2003 by Blei, Ng, and Jordan, topic models have been used across a wide range of commercial and scholarly domains. In the humanities, scholars have embraced topic modelling as a means of indexing and analysing large archival datasets of newspapers (Newman and Block 2006), government records (Miller 2013), novels (Jockers andMimno 2013, Tangherlini andLeonard 2013), and even poetry (Rhody 2012).…”

Section: Background and Motivationmentioning

confidence: 99%

“…Social scientists' interpretations of topic models are typically informed by domain expertise and grounded in knowledge of the texts from which the topics are derived. Many practitioners supplement their general knowledge the text with targeted readings of documents that are highly representative of each topic, and draw on these readings to validate or expand upon the 78 interpretation derived from the topic terms (DiMaggio, Nag, and Blei 2013, Marshall 2013, Miller 2013. In a similar manner, some practitioners also draw on document metadata.…”

Section: Qualitative Comparison Of Multiple Hyperperameter Configuratmentioning

confidence: 99%

“…For example, in a study of right-wing populism on social media,Stier et al (2017) derived a model of 100 topics but retained only 46 for the analysis. Taking this approach even further,Miller (2013) retained just six out of 50 modelled topics in his investigation of crime and unrest in China in the 18 th and 19 th centuries. Such selectivity, however, is not an option if the researcher is conducting an exploratory analysis, or wishes to describe the data in its totality.…”

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confidence: 99%

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Accounting for context in the use of topic models in social science: a case study exploring public discourse on coal seam gas in Australia

Veitch¹

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Probabilistic topic modelling is a machine learning technique that has recently begun to find application in the social sciences. With almost no human supervision, probabilistic topic models can infer the thematic structure of large textual datasets, making them an appealing tool for scholars in fields such as communication studies, where such datasets are increasingly common. However, topic models also present social scientists with a range of conceptual and practical challenges, many of which are yet to be satisfactorily resolved. Far from making life simpler for social scientists, the outputs of topic models can be bewildering, not only because of their complexity-a model may include dozens of topics, each of which is defined by dozens of terms-but also because of their multiplicity, since a topic model can produce not one, but infinitely many, subtly different sets of topics to describe a given dataset. Further difficulties arise from the complexity of the data itself: in social science, textual datasets often represent diverse assemblages of actors, and the meaning of the texts may depend on the circumstances of their production as much as on their textual content.xiii

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Rebellion, crime and violence in Qing China, 1722–1911: A topic modeling approach

Cited by 36 publications

References 3 publications

On the Relationship Between Firms and Their Legal Environment: The Role of Cultural Consonance

On the Relationship Between Firms and Their Legal Environment: The Role of Cultural Consonance

No Country for Neoliberalism: A Topic Modeling Approach to Protean Discourses to Resist Privatizations in Italy

Accounting for context in the use of topic models in social science: a case study exploring public discourse on coal seam gas in Australia

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