Text Analyses Research Articles

Exploring climate change discourses on the internet: a topic modeling study across ten years

This study examines online discourses about climate change using automated text analysis. Samples of web contributions from various sources, such as blogs, online newspaper articles, readers’ comments, tweets, and others, were collected in 2013, 2019, and 2023. The major themes people talk about when discussing climate change on the internet were identified using structural topic modeling. The study also explored how people discuss climate change differently when using different types of media channels and how the main themes change over time. Six major topics were identified for each point in time; associations between topics and media types were examined. Three topics emerged repeatedly: Dispute over the reality and the implications of climate change, discussions about aspects of the science of climate change, and discussions about causes and consequences of global warming such as sea level rise. In 2019 and 2023, the topic of action (what to do) and the topic of looming disaster showed up repeatedly. Topics limited to one specific corpus were policy discussions, debates about emissions, about renewable energies, about agricultural implications, and expressions of despair. The topical structure could be organized in two general groups, one group containing more science-related topics, and another group containing expressions of dispute, disagreement, and affect. A significant correspondence between media type and prevalent topic could be detected. Media such as Twitter/X and comments are dominated by dispute and despair expressions, whereas media such as blogs and journalistic online articles are primarily concerned with scientific topics in general, as well as with specific topics concerning global warming or renewable energies. In sum, we found noteworthy topical invariances across ten years, and systematic correspondences between topics and media types. The study contributes to the understanding of online discourses about climate change and highlights the role of media type in shaping these discourses.

Masculinity and Homosociality in Western Cinema: Taking Close (2022) as a Case Study

Masculinity and homosociality in Western cinema undergo continuous evolution, transitioning from the construction of traditional ideals to contemporary, more diverse expressions, thereby presenting challenges and deconstructions. To contribute to the theorization of masculinity and homosociality in Western films, this study examines Lukas Dhont's Close to analyze how masculinity and homosociality are represented and negotiated to reproduce gender structures and heteronormative ideologies, and offer implications for future film presentations. Employing textual and formal analyses, along with relevant theories of masculinity and homosociality, this paper identifies different forms of masculinities embodied in hierarchical and horizontal homosociality. In doing so, this paper finds that homosociality provides space for some masculinities to assert and solidify their dominance while relegating others to subordinated or marginalized positions. The dynamic shifts in masculinity also correspondingly affect homosocial dynamics. Further exploration is warranted in presenting and constructing positive narratives surrounding non-hegemonic masculinity and horizontal homosociality, so that a diverse, anti-homophobic, and gender equality-supporting masculinity on screen may have the potential to achieve hegemony.

Research on the Content Validity of the English Reading Test in Harbin Senior High School Entrance Examination

The Academic Test for the Junior High School Students, as a kind of academic level examination, plays a crucial role in the selection and streaming of talents at the secondary school level in China. Reading is an essential skill that language learners need to master, and it has a large proportion in the English test of the High School Entrance Examination (HSEE). Therefore, studying the validity of English Reading Test in the HSEE can not only provide the examiner of the HSEE with data references for judging the validity of the reading test, but also provide references for English teachers to innovate teaching methods, as well as cultivating the students' English reading strategies and achieving the overall improvement of the reading ability. Focusing on English Reading Test in Harbin HSEE (2019-2023), this research selects the framework of test characteristics proposed by Bachman and Palmer and analyzes discourse input and expected response to explore the content validity by using textual, quantitative and comparative analyses. The results show that English Reading Test in Harbin HSEE (2019-2023) has a certain degree of content validity and basically meet the requirements of the exam syllabus, but problems still exist. The presentation form of the test text is monotonous, the difficulty gradient is unreasonable and the assessment of reading skills is insufficient.

Assessment Tool of Portfolios: Enhancing Primary School Students' English Reading Proficiency

This study aims to explore the use of portfolios as an assessment tool to enhance primary school students' English reading proficiency. Portfolio assessment offers a more comprehensive and continuous approach compared to traditional assessment methods, which tend to measure students' abilities at a single point in time. By using portfolios, teachers can collect various types of student work that demonstrate their progress and understanding in reading, such as book summaries, text analyses, and personal reflections. This research employs a qualitative method. Data is collected through classroom observations, interviews with teachers, and analysis of students' portfolio documents. The findings indicate that using portfolios as an assessment tool provides several significant benefits. First, portfolios allow for a more holistic evaluation of students' reading abilities, encompassing various aspects such as text comprehension, critical analysis, and reflective skills. Second, portfolios offer students the opportunity to see and recognize their own progress, which can boost their motivation and confidence in learning. Overall, this study concludes that portfolios are an effective assessment tool for enhancing primary school students' reading proficiency in English. The use of portfolios not only aids in more comprehensive assessment but also supports deeper and more sustained development of reading skills. Therefore, it is recommended that schools and educators consider integrating portfolios into their English teaching curriculum.

The role of negative affect in shaping populist support: Converging field evidence from across the globe.

Support for populism has grown substantially during the past 2 decades, a development that has coincided with a marked increase in the experience of negative affect around the world. We use a multimodal, multimethod empirical approach, with data from a diverse set of geographical and political contexts, to investigate the extent to which the rising electoral demand for populism can be explained by negative affect. We demonstrate that negative affect-measured via (a) self-reported emotions in surveys as well as (b) automated text analyses of Twitter data-predicts individual-level populist attitudes in two global surveys (Studies 1a and 1b), longitudinal changes in populist party vote shares at general elections in Europe (Study 2), district-level Brexit voting in the 2016 U.K. referendum (Study 3), and county-level vote shares for Donald Trump in the 2016 and 2020 U.S. presidential elections (Studies 4a and 4b). We find that negative emotions-such as fear and anger as well as more often overlooked low-arousal negative emotions like depression and sadness-are predictive of populist beliefs as well as voting and election results at scale. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Second-level agenda-setting effects of news media and public policy on social media discourse across platforms: immigration during the COVID-19 pandemic in the U.S.

ABSTRACT Integrating intermedia, second-level agenda-setting, and cross-platform research, this study examines the role of news media attention and public policy decisions in driving the salience of issue attributes on multiple social media platforms. We collected three immigration-related datasets (i.e., social media posts, news media headlines, and policy documents covering the first year of the COVID-19 pandemic that also marked the last year of the Trump presidency) and applied manual coding, automated text analysis, and time series modeling to analyze the relationships. The results show that news media set the public agenda across Facebook, Twitter, and YouTube at the second level, with conservative media elevating travel-related discussion and liberal media driving border- and court-rulings-related discussion on those platforms. Compared to news media, the second-level agenda-setting effect of policy announcements was small and platform-specific. Among the three platforms, public discourse on YouTube was the most responsive to media and policy agendas. These findings advance second-level agenda-setting research, demonstrate partisan differences in news media’s impact, reveal the limited role of public policy, and provide a nuanced portrayal of cross-platform public discourse dynamics.

Assessing Illinois companion animal veterinarians' antimicrobial prescription practices and the factors that influence their decisions when treating bacterial infections in dogs and cats.

Judicious antimicrobial use in companion animal practice is critical for maintaining the effectiveness of antimicrobial agents against bacterial infections and reducing the selection of antimicrobial-resistant bacteria. This study aimed to provide insights into companion animal veterinarians' antimicrobial treatment recommendations for common bacterial infections in dogs and cats and describe the factors influencing their prescription choices. An online survey using QualtricsXM® software was administered between September and November 2022 to companion animal veterinarians who were Illinois State Veterinary Medical Association members. Descriptive and text analyses were conducted to assess the participants' responses. A total of 78 surveys were included in the analysis. Skin infections were ranked as the most common bacterial infections for which veterinarians prescribed antimicrobial agents, followed by ear, urinary tract, respiratory, and enteric infections. The severity of clinical symptoms and the results of bacterial culture and susceptibility tests were the most influential factors for veterinarians when making antimicrobial prescription choices. Veterinarians were aware of the current antimicrobial prescription guideline recommendations when prescribing antimicrobials empirically to nine hypothetical scenarios of bacterial infections. According to the results of the text analysis that assessed veterinarians' responses to an open-ended question, regarding their challenges when prescribing antimicrobial agents, the pairwise correlation of word frequencies within each response showed the highest correlations between the words 'owner' and 'compliance', 'administration' and 'route', 'cost' and 'culture', and 'patients' and 'acceptance'. The study results can support animal health stakeholders in the development of antimicrobial stewardship programmes to promote appropriate antimicrobial use and limit the emergence of antimicrobial resistance.

National constitutional courts’ use of the ECJ's precedents: The case study of Czechia

This article interrogates how Member States’ constitutional courts make use of the case-law of the European Court of Justice. Instead of focusing on the extreme instances of open backlash, we put forward a data-driven methodological approach to the study of Europeanization of national constitutional courts. Drawing on the use of automatic text analysis, we suggest that searching for the formal citations of the rulings of the European Court of Justice in the constitutional courts’ case-law contributes to nuanced understanding of their role within the EU. By means of a case study of the Czech Constitutional Court's case-law (more than 71 000 decisions issued between the years 2004 and 2022), we demonstrate a way to explore the so far under-researched area of EU law adjudication where the majority of strategic behaviour might be taking place.

Flowing Body: The Collision of Power Relations, Mind and Body Agency

This article constructs a novel theoretical framework for understanding the body in feminist theory by critically engaging with existing non-binary and non-essentialist views. It advances upon foundational critiques, particularly those by Haraway, Connell, and Butler, integrating the dynamics of body agency, power relations, and mind to propose a more fluid and intersectional approach to body politics. The new framework posits the body as an active participant in its continuous formation, interacting with and reshaping societal norms and expectations. Empirically, the paper analyzed four artworks displayed in art galleries and museums in Lund and Malmö in Sweden as case studies, focusing on how these works represent and shape notions of the female body across various themes including beauty, reproduction, migration, and sexuality. These artworks serve as a medium to explore how corporeal experiences are constructed through the interplay of power relations, mind, and body agency. Through critical analyses of theory and textual analyses of artworks, this paper points out that the body is a language of fluidity, simultaneously influenced and shaped by power relations, the mind, and its agency. Feminism should treat the body more carefully, avoiding biological essentialism or absolute social constructs.

Using Transfer Learning to Realize Low Resource Dungan Language Speech Synthesis

This article presents a transfer-learning-based method to improve the synthesized speech quality of the low-resource Dungan language. This improvement is accomplished by fine-tuning a pre-trained Mandarin acoustic model to a Dungan language acoustic model using a limited Dungan corpus within the Tacotron2+WaveRNN framework. Our method begins with developing a transformer-based Dungan text analyzer capable of generating unit sequences with embedded prosodic information from Dungan sentences. These unit sequences, along with the speech features, provide <unit sequence with prosodic labels, Mel spectrograms> pairs as the input of Tacotron2 to train the acoustic model. Concurrently, we pre-trained a Tacotron2-based Mandarin acoustic model using a large-scale Mandarin corpus. The model is then fine-tuned with a small-scale Dungan speech corpus to derive a Dungan acoustic model that autonomously learns the alignment and mapping of the units to the spectrograms. The resulting spectrograms are converted into waveforms via the WaveRNN vocoder, facilitating the synthesis of high-quality Mandarin or Dungan speech. Both subjective and objective experiments suggest that the proposed transfer learning-based Dungan speech synthesis achieves superior scores compared to models trained only with the Dungan corpus and other methods. Consequently, our method offers a strategy to achieve speech synthesis for low-resource languages by adding prosodic information and leveraging a similar, high-resource language corpus through transfer learning.

Kritik Pemerintah Pada Lagu “Gugatan Rakyat Semesta” Karya Feast (Analisis Wacana Kritis Model Norman Fairclough)

This research aims to examine the role of songs as a tool of criticism against the government, focusing on "Gugatan Rakyat Semesta" which calls for scrutiny of governance. The study employs Norman Fairclough's critical discourse analysis approach with textual, discursive, and sociocultural analyses to understand how the song reflects socio-political dynamics in Indonesia. At the textual level, the research indicates that the song explicitly or implicitly urges people to challenge the government. Discursively, there is a correlation between the release of the song and student demonstrations. Sociocultural analysis reveals that the song's release is influenced by social tensions arising from economic decline, unemployment, corruption, discourse on election postponement, and others. This research is expected to contribute to understanding how musical artworks, particularly songs, can serve as tools of critique in the Indonesian socio-political context.

The Role of Language in Emotions: A Pragmatic Analysis of the Naked Man’s Utterances during the Naira Scarcity in a Banking Hall in Nigeria

The unique socio-economic contexts known as trendy speech events take place especially in commercial banking halls as the result of a tensed political situation in Nigeria. Against this backdrop, this paper focuses on the use of speech act theory in pragmatics by a naked man to explicate the various illocutionary acts of the data for this study. The data comprises 45 sentences of the viral video used for this analysis. The mixed method design was adopted for this study. The qualitative method accounted for the content and the textual analyses, while the quantitative method was used for the percentile findings. The purposive random sampling technique was used to select utterances for this study to avoid redundancy and tautology typical of many spoken discourses. With the analysis of selected utterances using the speech act theory by J.R Searle, the findings revealed the speech acts express anger and frustration, they also assert, tell, describe, inform, remind, command, and make a request. Thus, the findings of the study recommended that linguistic communication should be carefully and appropriately done because the language use expresses more actions, emotions as well as intentions than what is actually expressed. Furthermore, the assertive showed that the speech acts of language users are capable of defining their different hidden emotions, personalities, and other intentions in different communicative contexts. This study is important as it unveils the understanding of communication in crisis situations, that is, how people communicate under stress and reveals how cultural and social factors influence communication styles.

The Performative Body in Ibsen’s A Doll House and Saput’s Sakambari: Rebelling and Reclaiming Women’s Power Dynamics

Henrik Ibsen's A Doll House, directed by Bernice Garfield-Szita and Prakash Saput's Sakambari showcase a similar performative body of women, resisting the patriarchal societal system despite having existed in two distinct spatiotemporal contexts. In this light, the paper comparatively examines the performative bodies of Nora in A Doll House and Sakambari in Sakamabari to analyze how their body acts serve as a site of submission and resistance simultaneously. In doing so, the study employs qualitative methods, mainly textual analysis for visual texts, lyrics, and dialogues in a multi-modal approach, using the Butlerian concept of gender performativity, "not biology but culture," and the Foucauldian concept of body and sexuality. It examines how the performing bodies epitomize submissive and resistive agencies for autonomy and justice. Nora's and Sakambari's performative bodies in different phases – the plain, commodified, and beyond – in one way to another challenge the masculine disposition and advocate for liberation. The analysis reveals that the two characters employ contrasting approaches to resisting the existing social structure. Nora exhibits direct submission and defiance, while Sakambari explicitly submits and implicitly resists. While both of them challenge the status quo of society, the performative bodies in different layers of resistance empower them to contest patriarchal societal foundations even though their paths to liberation differ from one another.

Illegal Online Gambling Site Detection using Multiple Resource-Oriented Machine Learning.

The COVID-19 pandemic has led to faster digitalization and illegal online gambling has become popular. As illegal online gambling brings not only financial threats but also breaches in overall cyber security, this study defines the concept of absolute illegal online gambling (AIOG) using a machine-learning-driven approach with information gathered from public webpages. By analysing 11,172 sites to detect illegal online gambling, the proposed model classifies key features such as URLs (Uniform Resource Locator), WHOIS, INDEX, and landing page information. With a combination of text and image analyses with machine learning-driven approach, the proposed model offers the ensemble combination of attributes for high detection performance with the verification of common attributes from metadata in online gambling. This study suggests a strategy for dynamic resource utilization to increase the classification accuracy of the current environment. As a result, this research expands the scope of hybrid web mining through constant updating of data to achieve content-based filtering.

Literacy and Financial Education: Private Providers, Public Certification and Political Preferences

AbstractFinancial education can influence the level of financial literacy. In many countries public authorities implement financial education policy by means of ex ante certification of both private and public providers of education activities. This article uses political economy, educational marketing and text analysis as complementary tools to offer a positive analysis of such setting. Being financial education a credence good and given the key assumption that financial literacy is a country state–contingent endowment that deteriorates, as a consequence of innovation, the third-party certification can be considered as a strategic governance solution. Yet, when a public agency acts as third-party certifier, political and bureaucratic incentives shape its action. In particular, political activism in financial education can be motivated by financial instability worries. Such theoretical relationship is empirically confirmed applying text analyses, and using financial education narrative as a proxy for activism both for the politicians of the European Parliament and the bureaucrats of the ECB in the period 1997–2024.

Catching up with climate priorities: Understanding multilateral development banks' evolving approach to biodiversity

AbstractA global consensus now recognises biodiversity as equal to climate change in its importance to sustainable development. While multilateral development banks (MDBs) have developed a strong emphasis on climate change, how do they approach biodiversity as a new priority? Current literature on MDBs' approach to climate change is prolific, but scholarship on biodiversity is scarce. Here, we compare MDBs' climate and biodiversity efforts in order to identify differences, analyze causes, and ultimately propose ways for MDBs to prioritise biodiversity. Methodologically, we analyze MDB documents in the form of policies, high‐level announcements, and strategies, in order to compare climate change and biodiversity across five aspects: Financing, policy, strategy, client requirements, and environmental reporting. Subsequently, we apply automated text analysis to examine mentions of climate change and biodiversity in annual reports. Focusing on the 10 largest MDBs, we find that across all five aspects, MDBs' prioritisation of biodiversity lags far behind that of climate change. From that, we recommend that biodiversity be prioritised by MDBs in three ways: By adopting an integrated strategic approach to environmental issues that goes beyond climate, by not only addressing biodiversity through safeguards but also through labeled projects, and by assigning targets as proportions of total financing.

Retrospective text and qualitative analyses of patient experience and management of vasomotor symptoms due to menopause: voices from the PatientsLikeMe community.

Vasomotor symptoms (VMS) due to menopause cause substantial burden and distress. Some women join online communities to share experiences and treatment outcomes through peer-to-peer interactions. This study describes women's experiences with VMS and symptom management on the PatientsLikeMe online support group. Mixed-methods research included women aged 40 to 65 years in the PatientsLikeMe community who were recruited using convenience sampling. Text from online posts by members was analyzed retrospectively using natural language processing. Relevant data, including numbers and percentages of women and frequencies of mentions, were summarized descriptively. Qualitative semistructured interviews were conducted; data, notes, and recordings were transcribed and deidentified and thematic analyses were performed. Demographic information was available from 1,614 accounts included in retrospective text analyses. Women had a mean age of 56.7 years; most were White (87.8%) and not Hispanic/Latino (90.2%). Hot flashes and night sweats were most commonly mentioned symptoms (n = 146). Of 16 women who were interviewed, 14 met the inclusion criteria, and their responses were included in the analysis. VMS impacted life quality in terms of physical (43%) and mental well-being (36%), social activities (21%), and productivity (14%). Symptom management included temperature regulation (43%), lifestyle changes (36%), over-the-counter Estroven (29%), hormone therapy (21%), and contraceptives (21%). Half of the women were surprised by symptom intensity and duration; many felt unheard by their healthcare providers. VMS have a substantial negative impact on multiple aspects of women's life. Management strategies for these symptoms vary widely, and many women feel unprepared for navigating the complex challenges of menopause.

Differentiated secularism: discourse shaping of immigrants from different religious backgrounds in the French media

This paper examines the mechanisms of differentiated discursive disciplining for immigrants of different religious backgrounds in the French media. Based on a sample of 120 articles on immigration in the French mainstream media, textual analyses and comparisons were conducted. Results show that influenced by religious factors, the French media use secularism as a tool to portray completely different images of immigrants through different discursive logics. Muslim immigrants present a paradoxically biased negative image in the French media discourse as a collection of invaders and the disciplined. In contrast, the media image of Ukrainian immigrants of Orthodox Christian background is positive on the whole, with a certain degree of deliberateness in the details of its construction. The difference in the symbolic characterization between Catholicism and Islam enables the exclusionary media discourse against Muslim immigrants. The paper also discusses French media discourse flaws and policy dilemmas. The logic of French media discourse is paradoxical in its inability to maintain an intact secularist identification and to effectively influence political issues to the detriment of promoting immigrant integration.

ArabBert-LSTM: improving Arabic sentiment analysis based on transformer model and Long Short-Term Memory.

Sentiment analysis also referred to as opinion mining, plays a significant role in automating the identification of negative, positive, or neutral sentiments expressed in textual data. The proliferation of social networks, review sites, and blogs has rendered these platforms valuable resources for mining opinions. Sentiment analysis finds applications in various domains and languages, including English and Arabic. However, Arabic presents unique challenges due to its complex morphology characterized by inflectional and derivation patterns. To effectively analyze sentiment in Arabic text, sentiment analysis techniques must account for this intricacy. This paper proposes a model designed using the transformer model and deep learning (DL) techniques. The word embedding is represented by Transformer-based Model for Arabic Language Understanding (ArabBert), and then passed to the AraBERT model. The output of AraBERT is subsequently fed into a Long Short-Term Memory (LSTM) model, followed by feedforward neural networks and an output layer. AraBERT is used to capture rich contextual information and LSTM to enhance sequence modeling and retain long-term dependencies within the text data. We compared the proposed model with machine learning (ML) algorithms and DL algorithms, as well as different vectorization techniques: term frequency-inverse document frequency (TF-IDF), ArabBert, Continuous Bag-of-Words (CBOW), and skipGrams using four Arabic benchmark datasets. Through extensive experimentation and evaluation of Arabic sentiment analysis datasets, we showcase the effectiveness of our approach. The results underscore significant improvements in sentiment analysis accuracy, highlighting the potential of leveraging transformer models for Arabic Sentiment Analysis. The outcomes of this research contribute to advancing Arabic sentiment analysis, enabling more accurate and reliable sentiment analysis in Arabic text. The findings reveal that the proposed framework exhibits exceptional performance in sentiment classification, achieving an impressive accuracy rate of over 97%.

Stick to the status quo? Music and the production of nostalgia on Disney+

This article examines the production of musical nostalgia in High School Musical: The Musical: The Series (2019–23), one of the first series created for Disney’s streaming platform. On one level, the series serves as a nostalgic extension of the High School Musical franchise in its setting and narrative construction, and a nostalgic continuation of the teen-musical genre in its idealised depiction of high-school life mediated through song. At the same time, this nostalgia is coupled with an emphasis on the show’s newness: the series transposes the original film to a new format—a self-referential, multi-episodic mockumentary—and occupies a different temporal world, in which nostalgia is technologically mediated and constructed as part of the diegesis. Focusing on music, as a primary sensory input for the evocation of nostalgia, this study explores how The Series capitalises upon this nostalgia/modernity dichotomy to structure its narrative and engender brand affinity. Drawing together textual analyses of audiovisual sequences and practitioner testimony from the show’s creatives, it demonstrates how The Series uses music to develop Disney’s brand, harnessing the technological and creative promise of the Company’s proprietary streaming service, whilst simultaneously employing nostalgic strategies to reaffirm the status quo in aspects of its narrative.