Valuing the local within the global: A discourse analysis of professional development in a U.S.-Kurdish transnational university partnership

In an effort to support higher education in developing countries, partnerships between U.S. and international universities have surged, raising questions concerning the social equity of such linkages. Using a New Literacy Studies approach to discourse analysis, online transcripts from one such university partnership were analyzed to determine how language was used to negotiate a more equitable partnership through the adaptation of the social context of professional development activities. Discourse analysis of three relevant linguistic markers in the data suggests that cultural perspectives on professional development influenced the language choices made by university partners, reshaping the power structure toward greater social equity, and aiding in the completion of joint professional development goals. Findings underscore the importance of drawing on local knowledges in planning for and conducting transnational university partnerships.

Analysis of recreational psychedelic substance use experiences classified by substance

Rationale and objectives Differences among psychedelic substances regarding their subjective experiences are clinically and scientifically interesting. Quantitative linguistic analysis is a powerful tool to examine such differences. This study compared five psychedelic substance report groups and a non-psychedelic report group on quantitative linguistic markers of psychological states and processes derived from recreational use-based online experience reports. Methods Using 2947 publicly available online reports, we compared Ayahuasca and N,N-dimethyltryptamine (DMT, analyzed together), ketamine, lysergic acid diethylamide (LSD), 3,4-methylenedioxymethamphetamine (MDMA), psilocybin (mushroom), and antidepressant drug use experiences. We examined word frequencies related to various psychological states and processes and semantic proximity to psychedelic and mystical experience scales. Results Linguistic markers of psychological function indicated distinct effect profiles. For example, MDMA experience reports featured an emotionally intensifying profile accompanied by many cognitive process words and dynamic-personal language. In contrast, Ayahuasca and DMT experience reports involved relatively little emotional language, few cognitive process words, increased analytical thinking-associated language, and the most semantic similarity with psychedelic and mystical experience descriptions. LSD, psilocybin mushroom, and ketamine reports showed only small differences on the emotion-, analytical thinking-, psychedelic, and mystical experience-related language outcomes. Antidepressant reports featured more negative emotional and cognitive process-related words, fewer positive emotional and analytical thinking-related words, and were generally not similar to mystical and psychedelic language. Conclusion This article addresses an existing research gap regarding the comparison of different psychedelic drugs on linguistic profiles of psychological states, processes, and experiences. The large sample of experience reports involving multiple psychedelic drugs provides valuable information that would otherwise be difficult to obtain. The results could inform experimental research into psychedelic drug effects in healthy populations and clinical trials for psychedelic treatments of psychiatric problems.

Linguistic Markers in Individuals With Symptoms of Depression in Bi-Multilingual Context

Depression has been identified as the most prevalent mental disorder worldwide. Due to the stigma of mental illness, the population remains unidentified, undiagnosed, and untreated. Various studies have been carried out to detect and track depression following symptoms of dichotomous thinking, absolutist thinking, linguistic markers, and linguistic behavior. However, there is little study focused on the linguistic behavior of bilingual and multilingual with anxiety and depression. This chapter aims to identify the bi-multilingual linguistic markers by analyzing the recorded verbal content of depressive discourse resulting from life situations and stressors causing anxiety, depression, and suicidal ideation. Different contextual domains of word usage, content words, function words (pronouns), and negative valance words have been identified as indicators of psychological process affecting cognitive behavior, emotional health, and mental illness. These findings are discussed within the framework of Beck's model of depression to support the linguistic connection to mental illness-depression.

Sentiment Analysis for Depression Based on Social Media Post by Using Natural Language Processing

Presently Research Center expresses that, 72% of public uses some sort of social media. More than 300 million individual experiences the depression and despondency, just a small amount of them get sufficient treatment. Discouragement is the main source of incapacity worldwide and almost 800,000 individuals consistently loss their life because of suicide. Suicide is the subsequent driving reason for death among teenagers. Our idea is to suggest solution for this problem. Social Media gives an extraordinary chance to change early depressions, especially in youngsters. Consistently, around 6,000 Tweets are tweeted per second, 350,000 tweets per minute, 500 million tweets each day and around 200 billion tweets each year. By using this rich source of data and information, can efficient model which provides report of person’s depression symptoms will be designed. In this model an algorithm that can examine Tweets Expressing self-assessed negative features by analyzing linguistic markers in social media posts.

Language Markers of Leadership in Political Discourse

Leadership as an indispensable element of social relations is an object of research within different schools of thought; however, its common understanding has not been developed yet. Different authors share the opinion that leadership includes authority, ability to lead, take decisions, influence people, organize and structure group interaction, unite people to achieve a goal. In linguistics it is studied in sociolinguistics, political and anthropological linguistics. In the research the authors aim at detecting special language markers of leadership in the speech of a political leader which are verbalized by language means of different language layers, while their choice depends on sociocultural codes shared by the leader, typical of certain linguoculture, age, social, professional group, and stipulated by individual features of the leader’s personality. Considering the existing approaches to linguistic markers analysis, the authors point out at the relevance of sociolinguistic and athropolinguistic approaches, as these markers lie in the area of intersection of social dialect and leader’s idiolect. On the material of the interview of V.V. Putin to NBC journalist the authors attempt to detect, describe and classify markers of leadership in the political leader’ discourse. To define the lexical means of verbalization of leadership the authors employ the theoretical insights of conceptual fields theory. Pragmarhetoric markers are studied through speech acts theory. The research proved the authors’ hypothesis that a leader’s speech contains a multi-level complex of language markers of leadership, i.e. lexical and pragmarhetoric units which express the phenomenon of leadership in the discourse of a political leader.

Post-Traumatic Growth and Identity Construction in Covid-19 Messages Delivered to the People of Ghana by President Nana Akuffo Addo

This work analyses post-traumatic growth in Covid-19 addresses delivered to the people of Ghana by President Nana Akuffo Addo. We draw on Post-Traumatic Growth Theory to explain how Akuffo Addo constructs a new identity for himself and the nation in order to navigate through the pandemic and forge an agenda of growth and prosperity for Ghana. The study employs a linguistic content analysis approach. The data consists of twenty different speeches from the president to the people. The speeches are first analysed and coded manually for the five main tenets of Post-Traumatic Growth (PTG) identified in the updates. Consequently, the linguistic markers that are used in reconstructing the Ghanaian identity in response to the pandemic are delineated and mapped to the goals of the president using the Linguistic Inquiry and Word Count 2015 (LIWC2015; Pennebaker et al., 2015) software; a vocabulary analysis tool. The analysis showed that there was a high prevalence of personal pronoun use, use of positive-emotion words, and cognitive-processing words. This confirms our hypothesis that linguistic markers can be used to detect PTG.

A Search for Discriminative Linguistic Markers in ICT Practitioner Discourse, for the Ex Ante Identification of Disruptive Innovation

<p>Disruptive innovations have the potential to disrupt markets, and drive them in new directions. A common problem faced by business organizations is identifying such disruptive innovations. From a managerial perspective, there is real value in being able to accurately identify disruptive innovations early in the product life-cycle, as it affords the organization the opportunity to put in place business strategies that leverage this information, to gain maximal competitive advantage. This investigation was undertaken to determine if linguistic markers could be identified in ICT practitioner discourse that could be used to discriminate between traditional business intelligence (BI) - the legacy or incumbent technology, and software-as-a-service (SaaS) BI - a new technology and candidate disruptive innovation. Quantitative content analysis undertaken using the tool Veneficium WordFrequencyCounter, was used to analyze written practitioner discourse identified from within the Industry Newsgroup file of LexisNexis Academic universe. Analysis was undertaken using attribute sets derived deductively from the academic literature, and inductively from the data itself, which provided both manifest and latent meaning of component words. Individual relative word associations with both the traditional BI and SaaS BI corpora were also analyzed. Analysis of the attribute set usage data provided evidence that manifest and latent word meaning remained consistent for the time period investigated in this study (2000 to 2012), and so could support the purpose of this study, and was suggestive of the fact that SaaS BI could be a disruptive technology. The study also identified that there was a significant difference in vendor and industry attribute set usage between the SaaS BI and traditional BI corpora, consistent with the Abernathy-Utterback model. Analysis of individual word associations with the traditional BI and SaaS BI corpora identified a number of word association patterns that could discriminate between traditional BI and SaaS BI that may be transferable to other technologies. A crossover event pattern was also identified (in which the word association pattern switches between the incumbent and new technology), which may be able to provide an indication that a technology innovation is, or is about to become, disruptive. This study contributes a new approach for investigating disruptive innovation, and highlights the potential of using content analysis of practitioner discourse to identify linguistic markers for disruptive innovation. The key contribution of the study is the observation that discriminative linguistic markers can in fact be identified, and that such markers appear to have predictive capabilities. That is, they may allow organizations to identify disruptive innovations ex ante.</p>