Quantitative Narrative Analysis Research Articles

Powerful or Powerless? Women’s Power Levels in Contemporary Chinese Films

This article aims to achieve an experiential study of cinematic representations of females in Chinese films through quantitative narrative analysis. Applied to a census of 360 Chinese films across various genres produced across 18 years (2001–2018) systematically selected on Mtime, we ask to what extent female characters in Chinese films are empowered? How is their power exercised? And what socio-cultural implications can be detected from the cinematic representations of women in the contemporary Chinese gender discourse? We aim to fill in the gap in Chinese cinema studies in which most scholarships focused on pre-2000 works, adopted qualitative textual and narrative analysis to interpret the representations of women in a particular genre or in typical cases, leaving the quantitative approach, particularly focusing on the post-2000 films, all but absent. We develop a systematic set of typologies, including 4 major power-level categories (power-over, power-to, power-with, and no-power) and 12 deuterogenic ones, which can be applied for future research on Chinese film and media studies. While women’s career success has been articulated with empowerment, independence, subjectivity, and ambition in the neoliberal rhetoric, our research reflects a more intricate relationship between cultural representations of women and power in contemporary Chinese films.

Processes and Practices Improvement of Sample Receiving Counter at Government Clinical Laboratory in Sri Lanka

Improving efficiency of a clinical laboratory service should be a first priority in healthcare development of any country. It plays a significant role as it facilitates diagnosing and treating diseases and finally to discharge the patients faster. Therefore, the reliability and the accuracy of a clinical laboratory should be guaranteed through a sound sample management. The aim of this study was to improve the process and practices of sample management at a sample receiving counter of a selected government clinical laboratory in Sri Lanka. The study was an institution based interventional project. The research adopted mixed methods including a desk review, a checklist, focus group discussions and a staff satisfaction survey which was conducted among Medical Laboratory Technologists. Proportions, percentages and means were calculated for quantitative data and narrative analysis was done for the analysis of qualitative data. The results indicated that the incidences of missing samples and request forms and sample handling time have been significantly reduced at post intervention. Performance of the routine counter activities including proper documentation, updating the notice boards, monitoring temperatures of sample storing refrigerators and consideration of rejection criteria in accepting the samples were significantly improved after the intervention. Staff satisfaction on overall sample handling process and practices was significantly improved after the intervention except the current practice of sample data management and facility availability to carry out duties. The study recommends modifying the counter layout with adequate expansion. It also recognized the necessity of implementing a Laboratory Information Management System for whole laboratory operation.

The actorness of the President of the Republic in Italian foreign policy: a quantitative narrative analysis of two case studies (1999–2013)

In this paper, we address the topic of policy actorness in Italian foreign policy to characterize the understudied role of the President of the Italian Republic (PoR). We apply quantitative narrative analysis (QNA) as the methodological tool of our study, answering two research questions to which the academic literature has so far produced limited responses: (a) whether the PoR can be considered a relevant actor in Italian foreign policy and (b) which factors can affect the Italian PoR’s relevance in foreign policy. Considering the Italian PoR’s Diary as the unit of analysis and source of data, we study the two crucial cases of Ciampi’s presidency (1999–2006) and Napolitano’s first presidency (2006–2013). QNA allows us to quantify and compare, while maintaining an actor-centred approach, the relations of the two PoRs with the most relevant actors in foreign policy. The results of our analyses highlight the relevance of the Italian PoR figure, identifying the main areas of influence of the Italian head of state and their changes over time. We conclude providing a few hypotheses to interpret the outcomes of our analyses on the PoR’s role in Italian foreign policy.

Модель миграции периферийных идеологических концептов: возможности системно-динамического анализа

The work is devoted to the urgent problem of the danger of the growth of extremist sentiments among young people caused by unpredictable changes in ideological attitudes (attitudes) in the group consciousness. Objectives: study of the dynamics of peripheral ideological concepts – one of the structural elements of ideology; identifying the trend of changes in the ideological attitudes of student youth on the example of the South of Russia; assessment of the predictive capabilities of the system dynamic analysis methodology for calculating the dynamics of ideological processes. An attempt was made to approbate the author's method of studying ideological attitudes, which could be conditionally called quantitative narrative analysis. The empirical base was made up of data from a survey of 2500 students in the South of Russia and the results of a five-year monitoring of the development of the ideological situation. The theoretical basis is the morphological approach to the study of ideologies by Michael Frieden and the concept of the cognitive-ideological matrix. In the development of this concept, the focus of the study was shifted from the morphology (structure) of ideologies to implicit processes occurring at the border of the cognitiveideological matrix and the social environment. As a result, a descriptive mental model of peripheral ideological concepts and a conceptual model of their migration based on the Bass diffusion model were built, performed in the AnyLogic simulation system. The result of the study was the identification of a left-liberal trend using narrative analysis, which had replaced the significant predominance of conservative and national-patriotic ideological attitudes in the group youth consciousness. It is concluded that the model of migration of peripheral ideological concepts, created using the method of system dynamics and mathematical statistics, significantly expands the possibilities of forecasting ideological processes, but has some limitations.

What’s in a text? Bridging the gap between quality and quantity in the digital era

The digital era has not only given us the world of big data, but the tools to deal with this mostly unstructured, mostly textual data: Natural Language Processing (NLP) tools. Yet, most humanists and social scientists do not work with big data. They do not deal with millions of documents. Literary critics’ corpora are the handful of works produced by an author. The historians’ primary source documents number in the tens, perhaps hundreds. Social scientists deal with tens or hundreds of transcripts of focus groups and in-depth interviews, or at most a few thousand media articles. And they analyze these data either qualitatively or quantitatively with a variety of manual or computer-assisted methodologies, from content analysis to frame analysis, discourse analysis, quantitative narrative analysis. But, once developed, at least some of the NLP tools of automatic textual analysis and the data analytics visualization tools, can be applied not just to big data but to small data as well. This paper illustrates how some of these tools can be used by focusing on a short first-person narrative. And the NLP tools reveal patterns of language use perhaps not immediately discernible, thus proving useful in the analysis of even small data. But understanding and interpreting these patterns requires knowledge way beyond the NLP tools themselves. Humanists and social scientists need not fear computer scientists; rather, they need to learn to take advantage of them. NLP tools lay a bridge between quality and quantity, with much to be gained from a constant interaction between distant and close reading.

Когнитивная коммуникация памяти и идеологии в аттитюдах студентов: возможен ли количественный нарративный анализ?

Когнитивная коммуникация памяти и идеологии в аттитюдах студентов: возможен ли количественный нарративный анализ?

Following in Jakobson and Lévi-Strauss' footsteps: A neurocognitive poetics investigation of eye movements during the reading of Baudelaire's 'Les Chats'.

Following Jakobson and Levi-Strauss [1] famous analysis of Baudelaire’s poem ‘Les Chats’ (‘The Cats’), in the present study we investigated the reading of French poetry from a Neurocognitive Poetics perspective. Our study is exploratory and a first attempt in French, most previous work having been done in either German or English (e.g. [2] [3] [4] [5] [6]). We varied the presentation mode of the poem Les Chats (verse vs. prose form) and measured the eye movements of our readers to test the hypothesis of an interaction between presentation mode and reading behavior. We specifically focussed on rhyme scheme effects on standard eye movement parameters. Our results replicate those from previous English poetry studies in that there is a specific pattern in poetry reading with longer gaze durations and more rereading in the verse than in the prose format. Moreover, presentation mode also matters for making salient the rhyme scheme. This first study generates interesting hypotheses for further research applying quantitative narrative analysis to French poetry and developing the Neurocognitive Poetics Model of literary reading [NCPM; 2] into a cross-linguistic model of poetry reading.

The power of the President: a quantitative narrative analysis of the Diary of an Italian head of state (2006–2013)

Many authors agree that the President of the Italian Republic is the head of state with the widest powers among parliamentary governments in Europe. Although several studies have sought to explain Why the President’s power may increase or decrease, a quantitative measurement of the phenomenon—able to answer questions also about the Who (the actors), How (the modalities) and How much (the consistency) of the phenomenon itself—has seldom been carried out by scholars. This paper seeks to answer these unanswered substantive questions by measuring the potential power of the Italian head of state in a crucial case—the first Presidency of Giorgio Napolitano (2006–2013)—by means of a quantitative narrative analysis (QNA) and a social network analysis of his Diary. This is done in a semi-automated way by using natural language processing (NLP) techniques, including regular expressions and named-entity recognition. As regards the methodological contribution of the paper, its aim is to demonstrate that QNA with NLP tools for semi-automated analysis of textual data can be considered an effective and reliable methodology for the empirical investigation of potential power, enabling a more widespread application of this technique in the quantitative analysis of topics related to the power approach—that some scholars consider otherwise obsolete—also at the comparative level.

Coexistence of Post-traumatic Growth and Post-traumatic Depreciation in the Aftermath of Trauma: Qualitative and Quantitative Narrative Analysis.

Objectives: Post-traumatic growth (PTG) and post-traumatic depreciation (PTD) can be defined, respectively, as positive and negative changes in the aftermath of trauma. These changes can be assigned to the following domains: personal strength, relating to others, new possibilities, appreciation of life, spiritual and existential change. The aim of this study was to explore the possibility that positive and negative effects of trauma can coexist and explore the categories of effect.Methods: 72 participants were asked to recount their experience of trauma and answer questions about how it had affected their thinking about themselves and the world. Participants’ narratives were analyzed by competent judges and using Linguistic Inquiry and Word Count.Results: The domains in which positive changes were most frequently observed were Personal Strength (26.09%), Relating to Others (24.22%), and Appreciation of Life (21.12%). Negative changes mainly affected Relating to Others (33.33%) and Personal Strength (23.33%). The results were confirmed by quantitative analysis of narratives: participants’ narratives of trauma and its consequences contained more words which expressing positive emotions (1.67%) than negative emotions (0.90%), paired-sample t(60) = 9.70, p < 0.001. There were correlations between the frequency of words referring to positive emotions and PTG, r(62) = 0.39, p < 0.01, and between the frequency of words referring to negative emotions and PTG, r(62) = 0.23, p < 0.05.Conclusion: PTG and PTD can coexist and they can be regarded as outcomes of two separate processes. The study results also suggest that although PTG and PTD can coexist, they may be considered different domains of psychological functioning.

Reading Shakespeare Sonnets: Combining Quantitative Narrative Analysis and Predictive Modeling -an Eye Tracking Study.

As a part of a larger interdisciplinary project on Shakespeare sonnets’ reception (1, 2), the present study analyzed the eye movement behavior of participants reading three of the 154 sonnets as a function of seven lexical features extracted via Quantitative Narrative Analysis (QNA). Using a machine learning-based predictive modeling approach five ‘surface’ features (word length, orthographic neighborhood density, word frequency, orthographic dissimilarity and sonority score) were detected as important predictors of total reading time and fixation probability in poetry reading. The fact that one phonological feature, i.e., sonority score, also played a role is in line with current theorizing on poetry reading. Our approach opens new ways for future eye movement research on reading poetic texts and other complex literary materials(3).

Unpacking Violent Contention: The Troubles in Northern Ireland, 1968–1972

ABSTRACT This paper systematically describes the different types of political violence that occurred in Northern Ireland between 1968 and 1972, examining how they interacted and fueled each other. To measure the level of political violence in Northern Ireland, traditional quantitative approaches use variables such as the number of conflict-related deaths, paramilitary attacks, or riots; the goal of this paper, instead, is to disaggregate acts of violent contention by actor, type, and target. Relying on Quantitative Narrative Analysis (QNA), all the violent actions perpetrated by the actors participating in the conflict have been recorded, coded, and analyzed. Three main types of violence in Northern Ireland are identified: a) protest-related violence—violent interactions among protesters, counterprotesters, and police before, during, and after mass demonstrations; b) sectarian violence—includes riots and clashes between members of the two main ethno-national communities; and c) armed conflict—violent actions by paramilitary groups and security forces. While originating from different conflict situations, these three types of violence affected each other, as they altered, and were altered by, the broader political context. Conceptual and methodological disaggregation of political violence are encouraged to better understand violent conflicts.

The Gutenberg English Poetry Corpus: Exemplary Quantitative Narrative Analyses

This paper describes a corpus of about 3000 English literary texts with about 250 million words extracted from the Gutenberg project that span a range of genres from both fiction and non-fiction written by more than 130 authors (e.g., Darwin, Dickens, Shakespeare). Quantitative Narrative Analysis (QNA) is used to explore a cleaned subcorpus, the Gutenberg English Poetry Corpus (GEPC) which comprises over 100 poetic texts with around 2 million words from about 50 authors (e.g., Keats, Joyce, Wordsworth). Some exemplary QNA studies show author similarities based on latent semantic analysis, significant topics for each author or various text-analytic metrics for George Eliot’s poem ‘How Lisa Loved the King’ and James Joyce’s ’Chamber Music’, concerning e.g. lexical diversity or sentiment analysis. The GEPC is particularly suited for research in Digital Humanities, Natural Language Processing or Neurocognitive Poetics, e.g. as training and test corpus, or for stimulus development and control.

Changes in stakeholder dynamics and salience during a mining disaster

The objective of the study was to illustrate the consequences of management oversight, as an element of poor corporate governance, of timeous stakeholder identification and engagement during a South African mining crisis. A secondary objective was to apply Quantitative Narrative Analysis (QNA), a methodology thus far mainly used in sociological research, to the understanding of this governance problem.An historical event in the South African platinum mining industry, the Marikana mining disaster, served as the unit of analysis for this case study. By utilising QNA, changes in stakeholder dynamics and salience were identified, based on available narrative from South African and UK newspaper articles spanning the period 1-24 August, 2012. The historical timeline of events and consequences were plotted, the main actors identified and the relationships between the actors and the events, mapped. A stakeholder analysis took the form of graphical stakeholder models, facilitating meaningful interpretation of the effects of the events that occurred. A typology of stakeholder categorisation was used to plot how the classification of stakeholders changed during the course of 24 days.The methodology used lays foundations for future methodological applications of QNA within stakeholder theory and presents opportunities for improved understanding of the impact of stakeholders on a company and on each other during a crisis event. The study contributes, practically, to an understanding of the importance of stakeholder identification and engagement during times of crises in order to assist leaders in engaging appropriately and timeously with different stakeholders groups, thereby promoting sound corporate governance.

Quantifying the Beauty of Words: A Neurocognitive Poetics Perspective.

In this paper I would like to pave the ground for future studies in Computational Stylistics and (Neuro-)Cognitive Poetics by describing procedures for predicting the subjective beauty of words. A set of eight tentative word features is computed via Quantitative Narrative Analysis (QNA) and a novel metric for quantifying word beauty, the aesthetic potential is proposed. Application of machine learning algorithms fed with this QNA data shows that a classifier of the decision tree family excellently learns to split words into beautiful vs. ugly ones. The results shed light on surface and semantic features theoretically relevant for affective-aesthetic processes in literary reading and generate quantitative predictions for neuroaesthetic studies of verbal materials.

What’s in the brain that ink may character ….

AbstractIn this theoretical paper, we would like to pave the ground for future empirical studies in Neurocognitive Poetics by describing relevant properties ofShakespeare’s 154 sonnetsextracted via Quantitative Narrative Analysis. In the first two parts, we quantify aspects of the sonnets’ cognitive and affective-aesthetic features, as well as indices of their thematic richness, symbolic imagery, and semantic association potential. In the final part, we first demonstrate how the results of these quantitative narrative analyses can be used for generating testable predictions for empirical studies of literature. Second, we feed the quantitative narrative analysis data into a machine learning algorithm which successfully classifies the 154 sonnets into two main categories, i.e. theyoung mananddark ladypoems. This shows how quantitative narrative analysis data can be combined with computational modeling for identifying those of the many quantifiable sonnet features that may play a key role in their reception.

A third road to the past? Historical scholarship in the age of big data

ABSTRACTIs a third passage to the past possible, beyond Elton's and Fogel's two roads of narrative history and scientific/quantitative history? One that would combine narrative history's focus on the event, on individuals and their actions, at a particular time and place, to scientific/quantitative history's emphasis on explicit behavioral models based on social-science theories? That is the question this article addresses. It illustrates a computer-assisted methodology for the study of narrative—quantitative narrative analysis (QNA)—that does just that. Based on the 5 Ws + H of narrative—Who, What, When, Where, Why, and How—QNA quantifies events without losing the event itself, without losing people behind numbers, diachronic time behind synchronic statistical coefficients. When used in conjunction with dynamic and interactive data visualization tools (and new natural language processing tools), QNA may provide a third unforeseen road to the past.

“The Brain Is the Prisoner of Thought”: A Machine-Learning Assisted Quantitative Narrative Analysis of Literary Metaphors for Use in Neurocognitive Poetics

ABSTRACTTwo main goals of the emerging field of neurocognitive poetics are (a) the use of more natural and ecologically valid stimuli, tasks and contexts and (b) providing methods and models allowing to quantify distinctive features of verbal materials used in such tasks and contexts and their effects on readers responses. A natural key element of poetic language, metaphor, still is understudied insofar as relatively little empirical research looked at literary or poetic metaphors. An exception is Katz et al.’s corpus of 204 literary metaphors by authors such as Shakespeare or Dylan Thomas, for which various rating data are available. We reanalyzed their corpus using a combination of quantitative narrative analysis, latent semantic analysis, and machine learning in order to identify relevant features of the metaphors that influenced the ratings. The combined application of computational tools sheds light on surface and affective-semantic features that co-determine the reception of poetic metaphors and successfully predicted the period of origin (i.e., early vs. late), authorship (e.g., Byron vs. Donne) and goodness ratings of the metaphors. The present results can be used for generating quantitative hypotheses or selecting and matching verbal stimuli in empirical studies of literature and neurocognitive poetics.

Business storytelling about energy and climate change: The case of Brazil’s ethanol industry

Climate change narratives often evoke scary scenarios. But in business discourses, the climate change narrative often emerges as an opportunity rather than a threat. This paper examines the predominant business storytelling ploys used by Brazil’s sugarcane industry association, UNICA to promote the industry as environmentally and socially responsible. We used both qualitative and quantitative narrative analysis to analyze thirty-five videos and multimedia presentations produced as part of UNICA’s marketing communications. Drawing on insights about tropes variously evoking hero stories, learning stories and horror stories, we conclude that the sugarcane industry has developed hero and learning stories that portray the sugarcane industry as a sustainable business and ethanol as a ‘green hero’, a green, renewable energy that helps reduce greenhouses gas emissions and thus saves humanity from climate change.

South African Post–Apartheid Transitional Remembrance Policy (1994–1999)

The paper presents results of the qualitative–to–quantitative narrative analysis of the transitional remembrance policy in South Africa during Nelson R. Mandela’s presidency. It refers to findings on the structure of political applications of historical interpretations to the issue of national identity reconstruction during democratisation. Therefore, the paper considers a degree in which remembrance story–telling was used to legitimise, justify, explain and promote the Rainbow Nation, the inclusive and non–racial vision of South Africa’s ’ideal self’ based on Archbishop Desmond Tutu’s theology of Ubuntu hoping. It investigated these relationships on eight levels – legitimisation of new elites, presence of former elites, transitional justice, social costs of transformations, promotion of new standards, the symbolic roles of democratisation, need for national unity and the new state’s identity in international politics. Moreover, the paper introduces a draft comparison with other cases of transitional remembrance policy – Chile, Estonia, Georgia, Poland and Spain – and it offers the structural model of the use of historical interpretations in South African transition, as well as discussing it with reference to the general model of the transitional remembrance policy.

Local security policies and the protection of territory: an analysis of the Italian experience (2007-2009)

This paper explores the territorial dimension of local security policies, with reference to the “Security Pacts” signed in Italy between 2007 and 2009. These Security Pacts are an innovative instrument introduced by the central government, aimed at changing the model of security governance at the local level. After describing how Security Pacts have spread, and which institutional actors have participated in them, this study aims at deepening the analysis of their territorial dimension. More specifically, the research question at the basis of this study focuses on the identification of factors that can explain why the pacts feature variations in numbers and types of public administration at different levels, and why they tend to acquire particular spatial configurations rather than others. Three hypotheses are tested based on empirical data (obtained using a Quantitative Narrative Analysis with the aid of Geographic Information Systems and other statistical tools) used to identify which variable may best explain the propensity to use such pacts to solve security-related issues in different areas of the country.