Text Analyses Research Articles

Assessing Sustainable Development Goal Alignment in Local Food Systems: Insights from an Automated Text Analysis of the Organizational Literature

There is growing interest in assessing local food systems to guide efforts toward sustainability and aligning these assessments with the United Nations’ 17 Sustainable Development Goals (SDGs). However, the complexity of portraying local food systems poses numerous challenges for local communities, and automated text analysis and artificial intelligence (AI) offer promising solutions. This study tested the use of an automated textual analysis to assess the alignment of the Mauricie region’s food system in Quebec, Canada, with the SDGs. The analysis examined 35 organizational documents from the region using an automated text analysis based on a list of keywords for each SDG. Initially, the analysis revealed that several initiatives in the Mauricie region covered specific SDGs quite well, such as eliminating hunger (SDG 2). Areas such as health and well-being (SDG 3) received moderate attention, while SDGs such as life below water and on land (SDGs 14 and 15) were less emphasized. When these results were presented to regional stakeholders, these stakeholders reported that the findings did not closely reflect their perceptions of the food system. This study confirms the potential of automated textual analysis and AI in assessing local food systems and underscores the parameters and challenges of accurately portraying sustainability in local food systems.

Bridging the gap: mapping co-creation methods for public health impact and innovation

Abstract Background Co-creation offers a promising approach to public health innovation, particularly for tackling complex issues. However, the lack of a standardized methodology limits its reliability and reproducibility, especially across diverse contexts. This study explores co-creation methods used by researchers and practitioners, aiming to shed light on their implications for public health. Understanding this methodological landscape can enhance the effective implementation of co-creation processes to address complex challenges. Methods Utilizing the Systematic Methods Overview approach, we examined co-creation methods. Data were gathered from the Health CASCADE Co-Creation Database and grey literature using an artificial intelligence-assisted recursive search strategy and a two-step screening process. We conducted textual, comparative, and bibliometric analyses to evaluate methodological underpinnings and relationships between methods. Results Analysis of 2,627 academic articles and grey literature sources identified over 900 co-creation methods. While surveys, focus groups, and group discussions were prevalent, participatory methods were underutilized. Notably, 91.3% of methods co-occurred, with a predominant combination of qualitative approaches. Furthermore, a significant discrepancy between research and practice was evident, with only 10.2% convergence. Conclusions This study revealed a critical gap between co-creation in research and practice, emphasizing the need to bridge this methodological divide for advancing co-creation as a reliable approach in public health. The over-reliance on qualitative methods raises concerns about tokenistic engagement and undermines meaningful public participation in co-creation. Addressing this trend is vital to preserve the essence of true co-creation and maximize its potential for addressing complex public health challenges. Key messages • Mapping the diverse methods of co-creation in public health reveals both richness and disparities in approach, from surveys to participatory methods. • Addressing the discrepancy between co-creation in research and practice is vital for establishing a reliable and effective approach to tackling public health challenges.

‘We are citizens, not fans’: frictions and negotiations in idolizing the nation in state propaganda

ABSTRACT State-dominated ‘ideotainment’ has become a global trend to enhance political persuasion. Broadening the geopolitical and ideological contexts of research could further enrich this field. This study analyzes the failed case of state-sponsored virtual idols ‘Jiangshanjiao’ (JSJ) and ‘Hongqiman’ (HQM) with attention to Chinese netizens’ critical responses, and further uncovers the erratic, diverse, and controversial aspects of Chinese fandom nationalism. In China, the Communist Party of China has tamed fandom culture to promote pro-governmental nationalist activism. However, this soft propaganda is sometimes counterproductive and has been underexamined. This study uses textual and critical discourse analyses to examine netizens’ posts, comments, and answers regarding the JSJ and HQM. The findings reveal the conflict between emerging civic spirit and notorious commercialism; the conflict between functional attachment embedded in constructive patriotism and affective attachment embedded in the hierarchy; and the complex negotiation between participatory nationalists, cautious patriots, and rational citizens about the boundaries of politics and entertainment.

An Analysis of the Conceptual Function of Facing the Sea with Spring Blossoms

Since Facing the Sea with Spring Blossoms has attracted widespread attention, many scholars have formed four interpretations from various perspectives, namely: the poem conveys the love of life and the pursuit of happiness; the poem is a deathbed poem, expressing the poet's despair of earthly life; the poet is a sad and bitter soul in pursuit of happiness; the poem is the poet's choice between “existence or destruction.” Poetry is the poet's choice between "existence or destruction," and he finally chooses to give up earthly happiness. Systemic functional grammar was founded by Halliday, who believed that language has three meta-functions: conceptual function, communicative function, and textual function, which are linked to the transitivity system, mood system, and thematic system. Since its inception, Systemic Functional Grammar has been applied to many text analyses, demonstrating its powerful interpretative power. Guided by this theory, the author conducted a conceptual-functional analysis of Facing the Sea with Spring Blossoms and found that there are 25 processes in the poem, including nine material processes, five mental processes, six relational processes, three verbal processes, and two existential processes. The author analyzed the three types of processes that are more typical in this poem and drew the following conclusions: first, happiness is an important theme for the poet; second, the poem is opened by me (the poet) choosing between two kinds of happiness; third, the poet finally chooses non-earthly happiness, i.e., “I only wish to face the sea, with spring blossoms.”

Rhythm and shift frequency of strategic renewal in Indonesian firm performance

Purpose This study aims to explore how manufacturing firms in emerging economies can effectively adjust the rhythm and shift frequency between exploitation and exploration renewal. The authors also examine how these strategic adjustments can significantly boost firm performance, offering insights into the dynamic process of strategic renewal. Design/methodology/approach This study analyzes annual reports of 127 Indonesian manufacturing firms from 2014 to 2019, applying both linear and curvilinear regression models to examine the hypotheses. Data on exploration and exploitation renewal were meticulously gathered using computer-aided text analysis, using targeted keywords to identify strategic renewal efforts. Findings The study shows that a rather irregular balance rhythm between exploitation and exploration renewal surprisingly enhances firm performance. A curvilinear relationship emerges as performance peaks when the shift frequency of renewal occurs about three times. This relationship optimizes the strategic renewal processes, emphasizing that firms need to remain agile and adaptable in today’s dynamic market environment. Originality/value This study leverages organizational learning to assess how the paradoxical dimensions of exploration and exploitation renewal impact firm performance. By focusing on the temporal transition of these tensions, it provides insights into optimizing the rhythm and shift frequency of renewal, transitioning from a static to a dynamic accord.

Emerging New Media Syntax, Violation of English Syntactic Rules, and Meaning Misrepresentations

A new variety of English syntax emerged with the new media. This study examines new media syntax to show instances of mindless violation of grammatical rules and the misrepresentation of meanings among student users of the new media. The study relies on selected social media posts. Descriptive survey, textual and content analyses, and interpretive techniques are employed. The analysis demonstrates that new media syntax, a corrupted or bastardized form of the English syntax, is characterized by syntactic deviations, grammatical violations, misrepresentation of meanings, and informal features, which affect the performance of students in English Language courses or subjects because most of them transfer the syntactic features of new media syntax to their formal compositions. The study concludes that the strained use of new media exerts adverse effects on English syntax and students’ writing and performance because they lose marks to the transferred features of new media syntax to the formal English syntax, which causes solecism, violation of grammatical rules and misrepresentation of meanings. Teachers are charged to consistently teach students how to use new media language for its associated informal contexts and purposes alone rather than mixing it with the formal variety in formal compositions.

Large Language Model in Creative Work: The Role of Collaboration Modality and User Expertise

Since the launch of ChatGPT in December 2022, large language models (LLMs) have been rapidly adopted by businesses to assist users in a wide range of open-ended tasks, including creative work. Although the versatility of LLM has unlocked new ways of human-artificial intelligence collaboration, it remains uncertain how LLMs should be used to enhance business outcomes. To examine the effects of human-LLM collaboration on business outcomes, we conducted an experiment where we tasked expert and nonexpert users to write an ad copy with and without the assistance of LLMs. Here, we investigate and compare two ways of working with LLMs: (1) using LLMs as “ghostwriters,” which assume the main role of the content generation task, and (2) using LLMs as “sounding boards” to provide feedback on human-created content. We measure the quality of the ads using the number of clicks generated by the created ads on major social media platforms. Our results show that different collaboration modalities can result in very different outcomes for different user types. Using LLMs as sounding boards enhances the quality of the resultant ad copies for nonexperts. However, using LLMs as ghostwriters did not provide significant benefits and is, in fact, detrimental to expert users. We rely on textual analyses to understand the mechanisms, and we learned that using LLMs as ghostwriters produces an anchoring effect, which leads to lower-quality ads. On the other hand, using LLMs as sounding boards helped nonexperts achieve ad content with low semantic divergence to content produced by experts, thereby closing the gap between the two types of users. This paper was accepted by D. J. Wu, information systems. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03014 .

"Such pushing and shoving… and the smell! Why ever would they allow these people in to the Academy” sociability and body language of Madrid's museums visitors (19th century)

In 1828 preparations were being made for the opening of the first public museum in Spain: the Royal Prado Museum. Along with the placement of the works of art and the control of their security, visitors were an essential part of the organisation of the establishment. Although the valued role of museums as democratisers of culture has been emphasised, more recent studies have observed that the first visitors to European museums were not from all social strata. This article aims to analyse the public museum as an arena of sociability and to investigate the involvement of social elites in both the control of access and the imposition of behavioural models within these "temples of the arts.” For this reason, this paper approaches the debate around the concept of citizenship. On the one hand, it explores the gradual opening of museums to all social classes and the social debates surrounding it. On the other hand, it analyses the use of the museum as a space of symbolic battle for the appropriation of these scenarios and the creation of exclusion dynamics to limit interactions between social classes. Therefore, the text analyses, among other sources of analysis, the body language of visitors. An object of study that has been understudied but which can offer us interesting answers.

Developing advanced citation skills: A mixed-methods approach to corpus technology training for novice researchers

In contrast with most existing corpus technology (CT) studies which focus primarily on general vocabulary and grammar learning, this study investigates the effectiveness of CT in addressing challenges encountered by novice researchers in improving an advanced linguistic skill in EAP writing: using reporting verbs to express rhetorical functions in citations in literature reviews. An eight-week CT training programme featuring a practical framework of the rhetorical functions of citations and utilising the Parallel EAP Corpora was implemented for 50 Chinese postgraduate students who were L2 English users. A mixed-methods approach was adopted. Paired-samples t-tests demonstrated statistically significant improvement with medium effect sizes in the frequency and diversity of reporting verb usage in citations, as well as in the complexity of expressing rhetorical functions of citations. These findings were further corroborated by corpus-aided descriptive statistical and textual analyses. Questionnaire data and interviews further revealed students' positive evaluations towards the training informed by the Parallel EAP Corpora, which facilitated participants' learning in various ways. These findings hold substantial value for EAP pedagogy, indicating that the incorporation of pedagogically sound CT training can significantly improve novice researchers’ development of academic discourse through nuanced citation practices and advanced rhetorical strategies for composing literature reviews.

If it ain’t broke, should you still fix it? Effects of incorporating user feedback in product development on mobile application ratings

How can firms utilize collective user feedback in reviews to better tailor their products to improve customer satisfaction? Based on an automated text analysis of 1,075,704 reviews and a content analysis of 3255 mobile application updates, observed over 460 apps’ first year on the market, this paper investigates the role of collective user feedback on user ratings during the process of developing successive mobile app generations. The results reveal that the rewards associated with responding to user feedback and the penalties due to ignoring this feedback can be substantial. The impact of the match/mismatch between user feedback and product development decisions depends on the topic of the feedback and the timing of the update. The findings provide app developers with guidance on the challenge of prioritizing possible development paths: (1) improve ratings by promptly matching user feedback that require new content or smooth functioning of the app; (2) avoid rating penalties by continuously improving existing content or ensuring compatibility with most recent operating systems and devices. The implications shed light on the fundamental question of whether and when to pro-act on or re-act to the voice of the customer.

Organizational sensemaking and environmental performance: A longitudinal study of publicly traded firms' sustainability reports

AbstractEnvironmental strategy research has often used organizational interpretation as a key lens for understanding how firms engage in sensemaking around natural environmental issues and environmental performance. This work has rarely empirically tested the proposed relationships of organizational interpretation in firms' sensemaking around environmental issues nor the relationship between firms' environmental sensemaking and environmental performance. We empirically test this relationship, capturing environmental sensemaking through computer‐aided text analysis (CATA) of published sustainability reports, and environmental performance with the Trucost environmental dataset. Mixed‐effects general linear modeling on a bespoke longitudinal dataset of 117 publicly traded companies from 2005 to 2018 reveals the three stages of the organization interpretation model of sensemaking—scanning, interpreting, and responding—align as expected. We also find firms' environmental scanning relates with year‐over‐year improvement in environmental performance, yet environmental interpreting correlates with worsening environmental performance. Additionally, larger firms and firms in industries with high carbon emissions gather more environmental data and exhibit more extensive environmental interpreting. This research provides insight for scholars by testing environmental sensemaking and exploring the boundary conditions of sensemaking and performance, and for practitioners and policymakers by offering a new framework for analyzing and interpreting sustainability reports and corporate environmental performance.

Phonological Error Analysis in Reading Arabic Texts by Ninth Grade Students at the Wustha Level, Nurus Salam Islamic Boarding School, Mentayan, Bantan Subdistrict, Bengkalis Regency

This study attempts to identify the causes that led to the phonological mistakes of the stressing side, pauses, tones, and intonations in the Arabic text read by students at the Nurus Salam Mentayan Resident House's 9th grade Wustha level. The error analysis approach is used in this investigation to track the development of Arabic text reading abilities. In addition to recording techniques, freely engaged dialectical methods and observation are used in data collection. The study's findings demonstrated 50 errors in the stressed speech in both the speech and the sentence. The pause happened when one spoke the ma`rifat phrases in a sentence or number when one spoke the word Qaul and the phrase that came from it, and when one spoke the words and responses. 43 reading tones do not match the word's meaning; 4) 32 intonations on the intonation tune do not match the sentence or number's context. Since intonations are uttered consistently without regard to meaning, they cannot convey the structure and meaning of numbers. Several variables contribute to the incidence of mistakes, such as: 1) When it comes to suprasegmental sounds, particularly stressing, pauses, tones, and intonation, teachers pay insufficient attention to them. 2) In theory, no subjects like ashwat can accept the super-segmental sound element. 3) The mother tongue heavily impacts the use of this suprasegmental noise, as the students' reading habits of Indonesians are also flat, meaning they ignore tone, intonation, stressing, and pauses.

Design and implementation of an automated web-based Igbo text analyzer using natural language processing (NLP) tools

Design and implementation of an automated web-based Igbo text analyzer using natural language processing (NLP) tools

Life Trajectories of the Russophone Speakers in Germany: 30 Years of Observation

This article presents a multifaceted portrait of immigrants to Germany from the post-Soviet states. The article traces the paths of two families over the course almost of a third of a century after immigration, focusing on language use and integration into the new environment. In-depth interviews conducted at various stages of the integration process and age-appropriate tests served as research material. The content, text, and lexical analyses, as well as a linguistic biography method, were used. The research included four generations of Russian Germans and Jews in each family. Russophones in Germany have not had an easy time integrating but, ultimately, have a positive attitude toward their adoptive country. The results show that the German language became the primary means of communication outside the family and partly within the family where Russian dominates among the second and third generations. The oldest generation (great-grandfathers and great-grandmothers) were fluent in German to some extent; those who moved at the age of 20–40 learned it sufficiently for their jobs; their children studied in German preschools and schools and became completely bilingual; and the great-grandchildren were born in Germany. The younger generations have fully integrated into German society, although strong connections with locals exist among the older generations too. Proficiency in the Russian language is still maintained even among the great-grandchildren’s generation, although not to the same extent as among the generation of young parents.

Effect of electricity policy uncertainty and carbon emission prices on electricity demand in China based on mixed-frequency data models

This paper first constructs the electricity policy uncertainty (EPU) in China with textual methods and analyses the effect of the EPU and carbon emission prices (CEPs) on the total electricity demand. This paper also forecasts the demand for electricity in China with three mixed-frequency data models. The results show that the EPU index efficiently captures the uncertainty of China's electricity policy. The effects of EPU and CEPs on electricity demand are significant, and incorporating them into the forecasting model will improve the accuracy and timeliness. Moreover, compared with the ARMA model and LSTM neural networks, mixed-frequency data models perform better in electricity demand forecasting.

Rhetorical Structures of Abstracts Written for TESOL International Conferences

Introduction: The current research aimed to investigate rhetorical move structures in abstracts written for TESOL international conferences by non-native speakers of English. Methodology: Sixty abstracts were collected from Vietnamese and Thai proceedings published by three universities. These abstracts were written for the TESOL conventions in the period 2018-2019. The study used the five-move scheme (I-P-M-R-D) adapted from Pho’s (2008) framework for move analysis with the assistance of the automatic text analysis and move occurrences soft wares AntMover and AntConc. Results: Results from the study showed that Methodology, Result, and Purpose sections played vital parts in abstract writing while Introduction and Discussion seized small portions in the corpus. While writing abstracts for TESOL conventions, the Method section is frequently repeated or embedded in the 60 target abstracts of the present study. The present study also indicated that the authors writing papers for TESOL conferences did not strictly follow the five-move sequence as expected due to word limitation and face-to-face mode of paper presentations at conventions. Non-linear move patterns were also recognized that are aligned with the findings of previous research studies. Conclusion: The findings of this study revealed that the abstracts written for TESOL international conferences in this research have followed the P-M-R order of an abstract rhetorical structure. This study's findings on rhetorical structures could be of great assistance in helping novice writers in composing well-structured abstracts for TESOL conferences.

EMFSA: Emoji-based multifeature fusion sentiment analysis

Short texts on social platforms often suffer from insufficient emotional semantic expressions, sparse features, and polysemy. To enhance the accuracy achieved by sentiment analysis for short texts, this paper proposes an emoji-based multifeature fusion sentiment analysis model (EMFSA). The model mines the sentiments of emojis, topics, and text features. Initially, a pretraining method for feature extraction is employed to enhance the semantic expressions of emotions in text by extracting contextual semantic information from emojis. Following this, a sentiment- and emoji-masked language model is designed to prioritize the masking of emojis and words with implicit sentiments, focusing on learning the emotional semantics contained in text. Additionally, we proposed a multifeature fusion method based on a cross-attention mechanism by determining the importance of each word in a text from a topic perspective. Next, this method is integrated with the original semantic information of emojis and the enhanced text features, attaining improved sentiment representation accuracy for short texts. Comparative experiments conducted with the state-of-the-art baseline methods on three public datasets demonstrate that the proposed model achieves accuracy improvements of 2.3%, 10.9%, and 2.7%, respectively, validating its effectiveness.

Machine Credibility: How News Readers Evaluate Ai-generated Content

The advent of AI-generated news as a novel form of content demands renewed attention toward modes of understanding reader perceptions. This research sought to answer: What evaluative criteria do readers use to perceive automated news content? To answer this, the study employed a two-phase survey methodology designed to elicit reader perceptions of AI-generated news. Phase 1 yielded 26 dynamic descriptor words and reflected broad social perceptions of AI. In Phase 2, a series of exploratory factor analyses (EFA) was conducted on results of a survey using the 26 items obtained in phase 1 to uncover underlying factors contributing to differences in how readers ranked articles based on the aforementioned descriptor words. In both phases, readers were informed at the beginning of the survey that the articles were generated using AI. The first set of exploratory factor analysis results were obtained using varimax rotation, which revealed five salient factors underlying the 26 descriptors labeled Quality, Engagement, Alienation, Effort, and Coherence. The second exploratory factor analysis used oblimin rotation, which contrastingly revealed nine salient factors, which were labeled Credibility, Prolixity, Engagement, Substance, Clarity, Alienation, Complexity, Effort, and Neutrality. When compared with the results of factor analyses for human-generated news content, the findings offer new constellations of terms that reflect the dimensions that readers attend to in articles attributed to artificial intelligence.

Inflation of crisis coverage? Tracking and explaining the changes in crisis labeling and crisis news wave salience 1785–2020

Abstract Has there been an inflation in crisis coverage in newspapers over the last centuries, and if so, what structural factors drive this change? We utilize computational text analyses along with our own signal detection algorithm to measure the presence of crisis keywords and the emergence of crisis news waves. An analysis of crisis coverage in The Times (U.K., 1785–2020, 183,239 news stories) shows that the share of coverage that uses crisis keywords has increased, though not steadily. The number and salience of crisis news waves tied to discernible events has increased at a slower pace. The hypothesized driving forces—government expansion, mediatization of politics, and the activity of crisis frame sponsors—explain the development well and allow accurate predictions even when ignoring time in the forecasting model. Crisis coverage seems to reflect not so much the problems society faces, but society’s identity, priorities, and outlook on the world.

Investigating Acoustic and Psycholinguistic Predictors of Cognitive Impairment in Older Adults: Modeling Study.

About one-third of older adults aged 65 years and older often have mild cognitive impairment or dementia. Acoustic and psycho-linguistic features derived from conversation may be of great diagnostic value because speech involves verbal memory and cognitive and neuromuscular processes. The relative decline in these processes, however, may not be linear and remains understudied. This study aims to establish associations between cognitive abilities and various attributes of speech and natural language production. To date, the majority of research has been cross-sectional, relying mostly on data from structured interactions and restricted to textual versus acoustic analyses. In a sample of 71 older (mean age 83.3, SD 7.0 years) community-dwelling adults who completed qualitative interviews and cognitive testing, we investigated the performance of both acoustic and psycholinguistic features associated with cognitive deficits contemporaneously and at a 1-2 years follow up (mean follow-up time 512.3, SD 84.5 days). Combined acoustic and psycholinguistic features achieved high performance (F1-scores 0.73-0.86) and sensitivity (up to 0.90) in estimating cognitive deficits across multiple domains. Performance remained high when acoustic and psycholinguistic features were used to predict follow-up cognitive performance. The psycholinguistic features that were most successful at classifying high cognitive impairment reflected vocabulary richness, the quantity of speech produced, and the fragmentation of speech, whereas the analogous top-ranked acoustic features reflected breathing and nonverbal vocalizations such as giggles or laughter. These results suggest that both acoustic and psycholinguistic features extracted from qualitative interviews may be reliable markers of cognitive deficits in late life.