Newspaper Data Research Articles

Representation of Stuttering in the United Sates Newspaper Media

The understanding of how stuttering is portrayed in the newspaper media has largely been ignored but plays a role in public perception of stuttering. A text pattern analysis, cross-sectional study was conducted based upon analyses of publicly available data. The text corpus were generated from the U.S. newspaper media during 1980–2018 (downloaded from the database U.S. Major Dailies by ProQuest). The text corpuses were analyzed using the Iramuteq software using the cluster analysis and Chi square tests. The newspaper data set had 970 texts (i.e., articles in the main corpus). The cluster analysis of the main corpus resulted in six clusters, which were named as: (1) music (2) sports (3) politics and economy (4) speech (5) cinema, and (6) general. The sub-corpus which was built based on aspects related to speech (i.e., cluster 4 in main corpus analysis) had 539 texts, which had at least one segment in sub-corpus. The cluster analysis of sub corpus resulted in four clusters, which were named as: (1) education and social support (2) personal aspects (3) aspects related to speech and (4) research and development. Time series analysis of clusters indicated a change in the pattern of information presented in newspaper media during 1980–2018. The study shows that stuttering has been presented in the media while discussing various elements including sports, arts and politics and economy, and speech. The aspects related to speech found media focuses on various elements including personal aspects, providing education and support, and providing new insights into research and development

The power to control: State forces’ action and student contentious politics in the Argentine educational field

Student movements in Latin America have historically been at the forefront of democratization and progressive social action. This article seeks to understand state-led protest control against students and their movements in Argentina in the last decades (1997–2007). By drawing on a database of contentious politics events in Argentina using newspaper data, analysis of secondary sources, and in-depth interviews of actors, it closely examines when, why, where, and how the state contains student protests and how the power relations between them and the state unfolds over time. A main finding underlying this study is that the nature of state repression of students is related to (a) the tactics being used, (b) the demands being made, (c) the actors that are protesting alongside them, and (d) the political party in power. The article shows how the associational ties between students, teacher movements, political parties, and other movements change during moments of economic crisis and political shifts in government, and how this, in turn, results in changes in state control. Against common sense understandings, we find that changes toward more politically ‘progressive’ governments do not necessarily imply less amount of repression even though the nature of state control changes.

Protesting that is fit to be published: issue attention cycle and nationalist bias in coverage of protests in Ukraine after Maidan

ABSTRACT There is an established tradition in social movement research to study protests through event datasets constructed from newspaper data. However, studies evaluating the magnitude of bias in newspaper reporting on protests have been largely confined to Western Europe and North America and have predominantly focused on time-invariant bias. I extend the past scholarship by analyzing the bias in online newspapers’ reports on protest events in Ukraine prior to and following the Maidan protests, focusing on issue attention cycles. I find that the number of mentions per protest event in the national media dropped after Maidan, while the coverage of ideological protests increased, indicating an issue attention cycle. The regional sources displayed less bias; however, they over-reported protests against separatism and Russian intervention. This presents researchers with a trade-off between using selective national outlets which adhere more to journalism standards and less selective regional outlets featuring more unpredictable patterns of bias.

Live or recorded? Reassessing the “decline of the highbrow arts” debate using European newspaper data, 1960–2010

ABSTRACT Recent scholarship has argued that the concept of highbrow culture is undergoing radical changes, both in content and modes of appropriation. We introduce a new layer to this debate by bringing to the fore the format of the cultural product, distinguishing between “live” cultural products (concerts, exhibitions, live shows) and “recordings” (distributable items such as books or music albums). Using culture sections of newspapers (The Guardian, Le Monde, ABC, El País, Helsingin Sanomat, Dagens Nyheter) from 1960 to 2010 (n = 11,775) we ask what role the format of the cultural product plays for the highbrow/non-highbrow trajectories over time. We show that highbrow coverage faces a relative decline, mostly explained by the expanding non-highbrow arts coverage. Moreover, coverage on live events decreases, while coverage of recordings grows. This trend reflects the highbrow/non-highbrow divide, revealing that the “decline of the highbrow” phenomenon is under closer scrutiny a “decline of the highbrow live event”.

Ground Truth OCR Sample Data of Finnish Historical Newspapers and Journals in Data Improvement Validation of a re-OCRing Process

The National Library of Finland (NLF) has digitized historical newspapers, journals and ephemera published in Finland since the late 1990s. The present collection consists of about 16.51 million pages mainly in Finnish and Swedish. Out of these about 7.64 million pages are freely available on the web site https://digi.kansalliskirjasto.fi/etusivu . The copyright restricted part of the collection can be used at six legal deposit libraries in different parts of Finland. The time period of the open collection is from 1771 to 1929. The last nine years, 1921–1929, were opened in January 2018. This paper presents briefly the ground truth Optical Character Recognition data of about 500 000 words that has been compiled at the NLF for development of an improved OCR process for the Finnish collection. We discuss compilation of the data generally and show results of the new OCR process in comparison to current OCR, using the ground truth data as an evaluation benchmark. We also show with real newspaper data of 30 years and 109 million words that the re-OCRing process is improving the quality of the OCRed data.

Automatic Marathi Text Classification

Multifold growth of internet users due to penetration of Information and Communication technology has resulted in huge soft content on the internet. Though most of it is available in English language, other languages including Indian languages are also catching up the race rapidly. Due to exponential growth in Internet users in India common man is also posting moderate size data on the web. Due to which e-content in Indian languages is growing in size. This high dimensionality of e-content is a curse for Information Retrieval. Hence automatic text classification and structuring of this e-content has become the need of the day. Automatic text classification is the process of assigning a category or categories to a new test document from one or more predefined categories according to the contents of that document. Text classification works for 14 Indian languages are reported in the literature. Marathi language is one of the officially recognized languages of Indian union. Little work has been done for Marathi text classification. This paper investigates Marathi text classification using popular Machine Learning methods such as Naïve Bayes, K-Nearest Neighbor, Support Vector Machine, Centroid Based and Modified KNN (MKNN) on manually extracted newspaper data from sport’s domain. Our experimental results show that Naïve Bayes and Centroid Based give best performance with 99.166% Micro and Macro Average of F-score and Modified KNN gives lowest performance with 97.16% Micro Average of F-Score and 96.997% Macro Average of F-score. The proposed work will be helpful for proper organization of Marathi text document and many applications of Marathi Information Retrieval.

Sparse Extended Redundancy Analysis: Variable Selection via the Exclusive LASSO

Extended Redundancy Analysis is a statistical tool for exploring the directional relationships of multiple sets of exogenous variables on a set of endogenous variables. This approach posits that the endogenous and exogenous variables are related via latent components, each of which is extracted from a set of exogenous variables, that account for the maximum variation of the endogenous variables. However, it is often difficult to distinguish between the true variables that form the latent components and the false variables that do not, especially when the association between the true variables and the exogenous set is weak. To overcome this limitation, we propose a Sparse Extended Redundancy Analysis via the Exclusive LASSO that performs variable selection while maintaining model specification. We validate the performance of the proposed approach in a simulation study. Finally, the empirical utility of this approach is demonstrated through two examples—one on a study of youth academic achievement and the other on a text analysis of newspaper data.

Contextual analysis and newspaper archives in management history research

Purpose The purpose of this paper is to reveal, how newspaper archives can support contextualisation in management history research by providing quantitative and/or qualitative, accurate, contemporary and cost-effective, data which is not always available elsewhere. Design/methodology/approach The paper comprises a literature review, which summarises research into contextual analysis and newspaper archive theory; combined with content and textual analysis of articles published in the Journal of Management History and Management and Organizational History (2013-2017). Findings The findings reveal that the concept of contextualisation is absent from recent management history articles and that few management historians use newspaper archival sources as a data collection strategy. Research limitations/implications There is compelling evidence to suggest that contextual analysis can – perhaps should – be incorporated into management historians’ research strategies because managerial organisations operate in open systems, which are influenced by external factors. Originality/value This paper juxtaposes two neglected aspects of management history research, contextuality and newspaper archives, and proposes that a key source for historic contextual analysis is newspaper data.

Performance based Machine Learning Algorithm for Topic Oriented Text Categorization

With the growth of societal news on the web, public opinions are given major importance in decision-making. Researchers of text-based mining have made number of evaluations and were diversified using different data mining methods so as to make the conclusions positive, negative and neutral. So, opinions of people are considered to mine the social information as people give superfluous interest to the reports. In this paper the newspaper data set is considered to find the opinion mining to evaluate the sentiment. Sentiment Analysis is used to compute the opinions of people before they judge on a particular issue. Machine Learning is one of the important approaches for analysis of sentiments. Different methods like Naïve Bayes, SVM, Maximum entropy and SLDA are used for classifying the sentiments. Predictions based on precision, f-measure, recall are done to determine which method best suits the classification.

Do 40-Year-Old Facts Still Matter? Long-Run Effects of Federal Oversight under the Voting Rights Act

In 2013, the Supreme Court struck down parts of the Voting Rights Act that mandated federal oversight of election laws in discriminatory jurisdictions, prompting a spate of controversial new voting rules. Utilizing difference-in-differences to examine the act’s 1975 revision, I provide the first estimates of the effects of “preclearance” oversight. I find that preclearance increased long-run voter turnout by 4–8 percentage points, due to lasting gains in minority participation. Surprisingly, Democratic support dropped sharply in areas subject to oversight. Using historical survey and newspaper data, I provide evidence that this was the result of political backlash among racially conservative whites. (JEL D72, J15, K16)

Showcasing Environmental Justice Movements from the South: Comparing the Role of Media in Bangladesh

When we think about the role of media in social movements, we identify media’s representation of the core grievance of the movement, traction of the movement in the media and its role in helping the movement. Using two examples from Bangladesh’s recent environmental justice movements, I show the changing role of media coverage on the movements, given the political opportunity structures available and discuss the differences between the cases. Using newspaper data and social media interactions, I compare the dynamics of media’s treatment of two movements, one against a proposed open cast coal mine in Phulbari, Dinajpur and another protesting against the establishment of a coal-fired power plant near Sundarbans. For the first case, I analyze the role of print media and for the second, both print and social media. I argue that both old and new media served as stages showcasing contested meanings of development, environmental injustice in both cases. However, I also show that the differences between the contribution in motivating the resistances by old and new media is different. However, both types of media, when appropriated by the capitalist interests can become weapons against the marginalized more often than it works as a space for upholding their voices.

Collecting Community Stories: Local Studies Collections and What They Can Tell You About the Community

Collecting Community Stories: Local Studies Collections and What They Can Tell You About the Community

Media messages and attitudes toward muslims and ethnic minorities: A panel study among ethnic majority adolescents in the Netherlands

In recent years, western media coverage is frequently filled with issues relating to Islam, which are unfavorable to Muslims. The attitudinal consequences of such media messages are widely discussed; however, empirical research is scarce. This study uses large-scale panel data on adolescents in combination with newspaper data and takes advantage of an extensive fieldwork period during which media salience of Muslims has fluctuated. All unmeasured time-invariant characteristics are accounted for by adopting a fixed-effects panel design. The results provide evidence of immediate attitudinal responses to media salience: the more media salience of Muslims on the day of survey participation, the more negative adolescents feel about Muslims. However, the results do not point toward a secondary transfer effect because media-induced negative attitudes toward Muslims were not transferred to ethnic minorities. Findings of this study advance current research by providing evidence for the effect of daily variations in media salience on attitudes.

The media’s coverage of ‘Closing the Gap’ in Australian education

ABSTRACT Since 2007, ‘Closing the Gap’ between Indigenous and non-Indigenous people has been an ambition of Australian state and federal governments in areas including education, employment, and health. This paper examines media responses to government policies aimed at closing the achievement gap in schools. The paper analyses print and online newspaper articles in national and capital city/state-based newspapers that reported on the implementation and success of Closing the Gap policies in Australia’s schools. The paper argues that media narratives are often based on NAPLAN results, data sourced from the MySchool website, or newspaper-created metrics that support their own narrative. This paper highlights the narratives being purported to readers via the selective nature of newspaper data, and subsequently how these narratives attempt to influence the public discourse.

Words are the New Numbers: A Newsy Coincident Index of the Business Cycle

ABSTRACTI construct a daily business cycle index based on quarterly GDP growth and textual information contained in a daily business newspaper. The newspaper data are decomposed into time series representing news topics, while the business cycle index is estimated using the topics and a time-varying dynamic factor model where dynamic sparsity is enforced upon the factor loadings using a latent threshold mechanism. The resulting index classifies the phases of the business cycle with almost perfect accuracy and provides broad-based high-frequency information about the type of news that drive or reflect economic fluctuations. In out-of-sample nowcasting experiments, the model is competitive with forecast combination systems and expert judgment, and produces forecasts with predictive power for future revisions in GDP. Thus, news reduces noise. Supplementary materials for this article are available online.

Mapping the Terrain: An Indonesian Business Perspective of the ASEAN Economic Community

Research Aims - This paper focuses on the institutions that the ASEAN Economic Community (AEC) project will affect. By employing institutional logics theory, this study scrutinizes academics and business practitioners as institutions and the cultural context embedded within them. Methodology - A mixed method of newspaper data analysis and semi-structured interviews was used to obtain comprehensive data from both sources. Research findings - The findings suggest a definite orientation gap between business practitioners, associations, and academics—the three groups have less information and contributions compared with the government and association influences. This study concludes that more participation is needed from these institutions, which are currently feeling “victimized” and excluded by the project. Originality - The originality of this paper lies in its application of institutional logics to business perspectives within an Indonesian context. The framework offers a holistic approach to how people are institutionalized based on their macro-, meso-, and micro-environments. Managerial implications in the Southeast Asian context - There has been a lack of communication and coordination amongst these institutions. Therefore, this study guides the related institutions and helps them to map their roles in enhancing the AEC project. Research limitations and recommendations - This research has two limitations: 1) the lack of literature in this field, and 2) and the difficulty in accessing information from the government institutions. The paper offers avenues for further research: additional variables regarding Indonesian norms and values as well as a method for extending the research to other ASEAN members.

Named Entity Recognition for Kannada using Gazetteers list with Conditional Random Fields

Named Entities (NEs) that exist in the sentences are essential to build Natural Language Processing (NLP) applications for Information Extraction (IE) from large corpora. However, generating a large corpus is challenging for resource poor languages, such as Kannada. Further, there is no annotated corpus available online. The challenges faced in annotating NEs with pre-defined classes are: It is morphologically joined with other words and the spelling variations are more frequent for Kannada words. Sentence structure varies according to morphology, parts of speech (pos) and chunking of a language. These parameters differ from one language to another. To address these challenges, a novel application system is proposed to identify NEs in Kannada using a large corpus of 73,676 tokens. The Named Entity Recognition (NER) system consist of a robust pos tagger and Noun Phrase (NP) chunker developed for generic data. Five gazetteer lists were created from many orthographic patterns for each word. Context information such as previous two words, next two words, word morphology and gazetteer lists were added to feature lists. An unigram-bigram template was designed and incorporated into Conditional Random Fields (CRFs) to generate conditional feature functions. The proposed system resulted in 86.85% and 71.01% f-measure for gold test data and newspaper data respectively.

Framing the Taxation-Democratization Link: An Automated Content Analysis of Cross-National Newspaper Data

Taxpaying constitutes a major opportunity for citizens to relate to their governments. Although it is true that paying taxes is a responsibility, it also entitles citizens to claim control over government spending, which may facilitate a greater democratization of a country’s political regime. Consistent with this reasoning, a growing body of scholarship has documented a positive relationship between the size of tax revenues extracted by the state and the adherence of the country’s regime to democratic values. What has been left underexplored is the role in this relationship of the media, a commonly available and relied-upon source of information about taxpaying for the public. This study offers a first contribution in this direction, by exploring the relationship between the nature of the political regime and the rhetorical construction of the concept of a taxpayer in the national press. Based on an automated content analysis of articles (N=24,969) published by ninety-two newspapers and news agencies in fifty-one countries using a set of pretrained and validated machine-learning algorithms, the study demonstrates that the less democratic a state is, the more likely it is for the national press to frame a taxpayer as a subordinate in a hierarchical relationship with the state, by discussing taxpaying in tax collection, rather than public spending, terms. The study furthers a more nuanced understanding of the place of the media in the taxation-democratization link and demonstrates the applicability of the supervised machine-learning approach to classifying frames in large cross-national samples of newspaper data.

Crossing languages – crossing discourses

AbstractRecent studies concerned with historical Germanisms have shown that public discourses in other languages often appropriate German loanwords as frames of reference to interpret political realities and influence collective attitudes. This paper intends to contribute to this new strand of research by investigating discursive transpositions of the historical GermanismKulturkampfin the donor language, German, and two host languages, Polish and English. Originally used mainly in reference to government attempts to reduce the influence of the Catholic Church in Prussia/Germany in the 1870s, this term has come to be used in German and other languages to signify conflicts in various political and cultural contexts. Adopting a triangulated and trilateral approach and the method of corpus-assisted discourse study (CADS), this paper examines the use ofKulturkampfin large collections of Internet and newspaper data in German, English and Polish. The results show how the meaning ofKulturkampfhas been discursively re-contextualised and appropriated to perform local ideological work in public discourses in the three different cultural contexts.

Do 40-Year-Old Facts Still Matter? Long-Run Effects of Federal Oversight under the Voting Rights Act

In 2013, the Supreme Court struck down parts of the Voting Rights Act that mandated federal oversight of election laws in discriminatory jurisdictions, prompting a spate of controversial new voting rules. Utilizing difference-in-differences to examine the Act's 1975 revision, I provide the first estimates of the effects of oversight. I find that preclearance increased long-run voter turnout by 4-8 percentage points, due to lasting gains in minority participation. Surprisingly, Democratic support dropped sharply in areas subject to oversight. Using historical survey and newspaper data, I provide evidence that this was the result of political backlash among racially conservative whites.