Linguistic Word Research Articles

A global community or a global waste of time? Content analysis of the Facebook site “Humans of New York”

ABSTRACT This paper explores how stories of everyday experiences in urban settings from around the world foster and sustain a community that seemingly transcends national borders. Given that both urban and online experiences are increasingly prevalent in modern life, surprisingly little attention is paid to how these experiences might foster a sense of community in an online setting. We use Facebook’s Humans of New York (HONY) site, analyzing over 130,000 text comments, to explore this question. We apply content analysis and text mining techniques, using the Linguistic Inquiry and Word Count (LIWC) software and multidimensional scaling (MDS) to visualize their latent patterns. Integrating Chayko’s theoretical model of “portable communities,” we find evidence suggesting the existence of a shared social context, of positive interaction, empathy, and support, irrespective of national boundaries.

US-VERSUS-THEM POLARIZATION IN THE US PRESIDENTIAL DEBATES OF 2000

Political discourse as a specific sign system in which the meaning depends on the speaker’s intention tends to portray participants in terms of “us” versus “them”, which makes “us-versus-them” polarization one of the main distinguishing features of political discourse. The onset of the 21st century is a turning point in the history of geopolitics, which requires politicians to be more creative in search of vote-winning means. The pragmasemantic approach allows to study presidential debates between 1. Bush and Al Gore from the standpoint of semantics which studies meaning and which has been recently affected by pragmatics that deals with non-linguistic aspects of meaning such as the context of a situation and the speaker’s intention. The presidential debates of 2000 are a vivid illustration of how two opposing politicians strive to share the same objective though different language means. The contentanalysis program LIWC (Linguistic Inquiry and Word Count) was used in order to verify the results of research. The analysis of Pronouns, Positive/Negative Emotions, and Tense Focus through LIWC makes a contribution to political discourse studies. This article illustrate how various language means such as use of pronouns “we” and “they”, specific vocabulary and slogans, when grouped together, can appear to be an efficient research tactic.

THE LINGUISTIC WORLD VIEW OF BALLADS WRITTEN IN ENGLISH. NATIONAL AND CULTURAL PECULIARITIES

The article deals with the study of linguistic word view representation of national and cultural peculiarities in the texts of ballads written in English. National and cultural constituents are formed under the influence of factors connected with cultural tradition, social situation, and society life environment. The language records the historical experience of every nation’s assimilation in the world, which is determined by the culture and reflects its national peculiarities. It is presented in genre modifications of ballads and realized in some differences of lexical nominations of objects, phenomena and processes of the reality. Representatives of different national cultures have different ways of the reality realization and evaluation. It is proved by the results of cognitive and creative activities which are fixed in the linguistic representation of basic meanings in literary texts.

Understanding the Role of Language in Conflict

The purpose of this article is to illustrate innovations in text analysis associated with understanding conflict-related communication events. Two innovations will be explored: LIWC (Linguistic Inquiry and Word Count), the text modeling program from the open-source data analysis software program R, and SPSS Modeler. The LIWC analysis revisits the 2009 study by Donohue and Druckman and the 2014 study by Donohue, Liang, and Druckman focusing on text analyses of the Oslo I Accords between the Palestinians and Israelis to illustrate this approach. The R and SPSS modeling of text analysis use the same data set as the LIWC analysis to provide a different set of pictures associated with each leader’s rhetoric during the period in which the Oslo I accords were being negotiated. Each innovation provides different insights into the mind-set of the two groups of leaders as the secret talks were emerging. The implications of each approach in establishing an understanding of the communication exchanges are discussed to conclude the article.

Examining the Causes and Consequences of Confession-Eliciting Tactics during Interrogation

Research suggests interrogation techniques used by U.S. law enforcement can yield false confessions. To investigate, participants (n = 151) were randomly assigned to complete one of two simulated interrogation exercises designed to model different interrogation tactics: (a) the accusatorial Reid Technique, one of the most widely-used interrogation approaches by U.S. law enforcement; or (b) the information-gathering "Compliance" model. False confession rates were examined. The underlying emotional and cognitive themes in participants’ written confessions and open-ended responses were also examined using the Linguistic Inquiry and Word Count (LIWC) and Automated Integrative Complexity systems. Results revealed no differences in false confession rates between conditions. However, participants exposed to Reid-based questioning used comparatively more negative, angry, and close-minded (cognitively simple) language when describing their interrogator and less certainty in confessions. The emergent differences in emotional and cognitive reactions inform our understanding of the effects of interrogation approaches used by law enforcement in the United States.

Coding communication in consultation: Accurate, reliable, and efficient analysis.

Given the importance of consultation in school psychology practice, more research is needed to examine the types of interpersonal communication through which consultation is effective. This study revisited Erchul and Schulte (1990), which investigated the amount of transcription and coding of consultation sessions required for reliable and accurate estimates of particular consultation communication variables. Using Linguistic Inquiry and Word Count, this study examined tone, interrogatives, clout, affect, and use of the 1st-person plural pronoun within the instructional consultation, assessment, and teaming process. Results partially aligned with Erchul and Schulte in that tone, interrogatives, and clout could be reliably and accurately assessed by analyzing 1 complete consultation session or segments of 2 sessions. Affect and pronoun use could not be reliably and accurately measured by sampling segments of consultation sessions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Creating and Testing Specialized Dictionaries for Text Analysis

Practitioners in many domains–e.g., clinical psychologists, college instructors, researchers–collect written responses from clients. A well-developed method that has been applied to texts from sources like these is the computer application Linguistic Inquiry and Word Count (LIWC). LIWC uses the words in texts as cues to a person’s thought processes, emotional states, intentions, and motivations. In the present study, we adopt analytic principles from LIWC and develop and test an alternative method of text analysis using naïve Bayes methods. We further show how output from the naïve Bayes analysis can be used for mark up of student work in order to provide immediate, constructive feedback to students and instructors.
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 Boot, P., Zijlstra, H., & Geenen, R. (2017). The Dutch translation of the Linguistic Inquiry and Word Count (LIWC) 2007 dictionary. Dutch Journal of Applied Linguistics, 6(1), 65-76.
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 Massó, G., Lambert, P., Penagos, C. R., & Saurí, R. (2013, December). Generating New LIWC Dictionaries by Triangulation. In Asia Information Retrieval Symposium (pp. 263-271). Springer, Berlin, Heidelberg.
 Newman, M., Groom, C.J., Handelman, L.D., & Pennebaker, J.W. (2008). Gender differences in language use: An analysis of 14,000 text samples. Discourse Processes, 45(3), 211-236.
 Pennebaker, J.W., Boyd, R.L., Jordan, K., & Blackburn, K. (2015). The development and psychometric properties of LIWC 2015. Austin, TX: University of Texas at Austin.
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 Van Wissen, L., & Boot, P. (2017, September). An Electronic Translation of the LIWC Dictionary into Dutch. In: Electronic lexicography in the 21st century: Proceedings of eLex 2017 Conference. (pp. 703-715). Lexical Computing.

The long and short of it

AbstractPlacenames (toponyms) give insight into relationships involving people, place, and language. An exemplary placename derived from long-term engagement within the sensitive linguistic ecology of Norfolk Island in the South Pacific is used to detail how a fusing of linguistic analysis, words, and cultural memory is beneficial for what constitutes an ecolinguistic fieldwork methodology. Differences between the ethnographic method and an ecolinguistic fieldwork methodology are presented. This enduring and keyed-in commitment with Norfolk Island’s social and natural surroundings offers significant perceptiveness into and suggestions about how prolonged ecolinguistic work can be beneficial to language documentation projects, particular those incorporating lexical (word) and semantic (memory) description.

Hidden in the Figures: What Students Are Telling Us About the Effectiveness of Astrobiology Outreach.

Astrobiology is an ideal context to engage students with the processes of science. However, there is a problem in measuring the effectiveness of engaging students with astrobiology where the learning outcome is aimed at improving student views of science. Most studies suggest little to no change in students' views of science, especially in short experiences of hours or days. These studies mostly use quantitative methods, such as numerical scores derived from survey rating scales and responses. We propose that hidden in those figures, the words of students in written survey responses are telling us about the effectiveness of astrobiology outreach at improving understanding of science. We sampled 483 students from multiple high schools involved in an established astrobiology outreach program in Australia, using pre- and postintervention data collected from an open- and closed-form survey to identify the impacts of the program on students' views of science. We applied both conventional quantitative score analysis methods and computer-based qualitative analysis methods-NVivo and Linguistic Inquiry and Word Count (LIWC) programs. While there was little difference in postsurvey scores, there is evidence in the qualitative data that the astrobiology program creates cognitive conflict in students, a trigger to the learning process that can open students to the first steps in understanding the creative, subjective, and tentative nature of science.

Identifying Suicide Notes Using Forensic Linguistics and Machine Learning

This paper presents how to identify the characteristic properties of suicide notes using the analysis methods in forensic linguistics and how to apply the knowledge to the machine learning research. For this purpose, a corpus was compiled with Virginia Woolf’s literary works and suicide notes, which contained six texts. Then, each text was analyzed with the LIWC (Linguistic Inquiry and Word Count) software. Since the analysis results were complicated, a dimensionality reduction was conducted using a Principal Component Analysis (PCA). In the PCA analysis, it was found that, even though all the texts were written by the same author, the suicide notes were clearly identified from the literary works. The analysis results of LIWC analyses were applied to a machine learning technique (especially a Support Vector Machine; SVM), and the classification accuracy was measured using six real texts and three hypothetical texts. Through the analysis, it was found that the SVM machine identified the suicide notes from the literary works with 100% of accuracy. The current study demonstrates that the linguistic properties of texts can be used to identify the suicides notes from the other types of writings and that they can be used in machine learning research.

Languages for different health information readers: multitrait-multimethod content analysis of Cochrane systematic reviews textual summary formats

BackgroundAlthough subjective expressions and linguistic fluency have been shown as important factors in processing and interpreting textual facts, analyses of these traits in textual health information for different audiences are lacking. We analyzed the readability and linguistic psychological and emotional characteristics of different textual summary formats of Cochrane systematic reviews.MethodsWe performed a multitrait-multimethod cross-sectional study of Press releases available at Cochrane web site (n = 162) and corresponding Scientific abstracts (n = 158), Cochrane Clinical Answers (n = 35) and Plain language summaries in English (n = 156), French (n = 101), German (n = 41) and Croatian (n = 156). We used SMOG index to assess text readability of all text formats, and natural language processing tools (IBM Watson Tone Analyzer, Stanford NLP Sentiment Analysis and Linguistic Inquiry and Word Count) to examine the affective states and subjective information in texts of Scientific abstracts, Plain language summaries and Press releases.ResultsAll text formats had low readability, with SMOG index ranging from a median of 15.6 (95% confidence interval (CI) 15.3–15.9) for Scientific abstracts to 14.7 (95% CI 14.4–15.0) for Plain language summaries. In all text formats, “Sadness” was the most dominantly perceived emotional tone and the style of writing was perceived as “Analytical” and “Tentative”. At the psychological level, all text formats exhibited the predominant “Openness” tone, and Press releases scored higher on the scales of “Conscientiousness”, “Agreeableness” and “Emotional range”. Press releases had significantly higher scores than Scientific abstracts and Plain language summaries on the dimensions of “Clout”, and “Emotional tone”.ConclusionsAlthough the readability of Plain language summaries was higher than that of text formats targeting more expert audiences, the required literacy was much higher than the recommended US 6th grade level. The language of Press releases was generally more engaging than that of Scientific abstracts and Plain language summaries, which are written by the authors of systematic reviews. Preparation of textual summaries about health evidence for different audiences should take into account readers’ subjective experiences to encourage cognitive processing and reaction to the provided information.

THE REAL-WORLD-SEMANTICS INTERPRETABILITY OF LINGUISTIC RULE BASES AND THE APPROXIMATE REASONING METHOD OF FUZZY SYSTEMS

The real-world-semantics interpretability concept of fuzzy systems introduced in [1] is new for the both methodology and application and is necessary to meet the demand of establishing a mathematical basis to construct computational semantics of linguistic words so that a method developed based on handling the computational semantics of linguistic terms to simulate a human method immediately handling words can produce outputs similar to the one produced by the human method. As the real world of each application problem having its own structure which is described by certain linguistic expressions, this requirement can be ensured by imposing constraints on the interpretation assigning computational objects in the appropriate computational structure to the words so that the relationships between the computational semantics in the computational structure is the image of relationships between the real-world objects described by the word-expressions. This study will discuss more clearly the concept of real-world-semantics interpretability and point out that such requirement is a challenge to the study of the interpretability of fuzzy systems, especially for approaches within the fuzzy set framework. A methodological challenge is that it requires both the computational expression representing a given linguistic fuzzy rule base and an approximate reasoning method working on this computation expression must also preserve the real-world semantics of the application problem. Fortunately, the hedge algebra (HA) based approach demonstrates the expectation that the graphical representation of the rule of fuzzy systems and the interpolation reasoning method on them are able to preserve the real-world semantics of the real-world counterpart of the given application problem.

Reading Traffic Signs While Driving: Are Linguistic Word Properties Relevant in a Complex, Dynamic Environment?

When driving a vehicle, do we read the words displayed on traffic signs just as we do in more standard conditions? In the driving context, stimulus quality is generally worse, and reading has to be performed at the same time as we are doing other tasks. In the present work, we examined the effects of word frequency and word length on reading in such circumstances. A stimulus presentation mimicking the approach to the traffic sign increased the effect of word frequency, but not the effect of word length, on reading latency. In addition, performing the reading task while driving along a simulated route produced similar results. Therefore, in the context of the driving activity, the advantage of high-frequency over low-frequency words seems to be even more relevant than in standard conditions. Traffic sign designers can consider these results when deciding the most appropriate word in a variable message sign.

Multichannel image contrast enhancement based on linguistic rule-based intensificators

This study follows the direct approach to image contrast enhancement, which changes the image contrast at each its pixel and is more effective than the indirect approach that deals with image histograms. However, there are only few studies following the direct approach because, by its nature, it is very complex. Additionally, it is difficult to develop an effective method since it is required to keep a balance in maintaining local and global image features while changing the contrast at each individual pixel. Moreover, raw images obtained from many sources randomly influenced by many external factors can be considered as fuzzy uncertain data. In this context, we propose a novel method to apply and immediately handle expert fuzzy linguistic knowledge of image contrast enhancement to simulate human capability in using natural language. The formalism developed in the study is based on hedge algebras considered as a theory, which can immediately handle linguistic words of variables. This allows the proposed method to produce an image contrast intensificator from a given expert linguistic rule base. A technique to preserve global as well as local image features is proposed based on a fuzzy clustering method, which is applied for the first time in this field to reveal region image features of raw images. The projections of the obtained clusters on each channel are suitably aggregated to produce a new channel image considered as input of the pixelwise defined operators proposed in this study. Many experiments are performed to demonstrate the effect of the proposed method versus the counterparts considered.

Disagreeable Rhetoric, Shaming, and the Strategy of Dissenting on the U.S. Supreme Court

Why do U.S. Supreme Court justices direct caustic rhetoric against each other in their opinions? In this article, I test two alternative theories for the use of this rhetoric. The coalition maintenance hypothesis maintains that the rhetoric is a shaming mechanism directed against close colleagues to impose costs on dissensus, while the polarization hypothesis suggests that it is a consequence of the rise of affective polarization on the Court. Using an augmented version of the Supreme Court Database, supplemented with Linguistic Inquiry and Word Count (LIWC) data, as well as other original data, I find evidence for both models, with the coalition maintenance hypothesis more prevalent in recent terms. While there is evidence that the justices deploy caustic rhetoric against their ideological opponents, on the Roberts Court the justices have tended to use this rhetoric strategically to shame close colleagues who are voting against coalitional preferences.

Interval data driven construction of shadowed sets with application to linguistic word modelling

The interval data from different surveyed persons for one linguistic word can reflect the intra- and inter-uncertainties of the word. This study shows how to construct shadowed set models for linguistic words based on the surveyed interval data. Firstly, corresponding to the popularly used fuzzy sets for linguistic words, four kinds of shadowed sets are introduced according to their shapes and named as the normal, the left-shoulder, the right-shoulder, and the non-cored shadowed sets. A data-driven approach that utilizes different statistics to determine the shapes and parameters of the shadowed set models is then proposed. The proposed data-driven approach includes two methods; the first is the tolerance limit method depending on the mean and standard deviation of the remaining interval data after pre-processing, whilst the other is the percentile method relying on the percentiles of the remaining interval data. Additionally, to evaluate the modelling performance, three novel indices are presented to measure the uncertainty-capture capability and accuracy of the constructed shadowed set models. Finally, the proposed approach is applied to two real-world problems. One is the modelling of 32 words in a codebook, and the other is the modelling of the thermal feeling words. The proposed methods are compared with other interval data driven methods, e.g. the enhanced interval approach and the fuzzy statistic method. Our results show that the proposed percentile method performs better in both applications. The proposed approach can also be applied to some other linguistic word modelling applications when it is reasonable to adopt shadowed sets as the words’ models.

Informational Needs of Urinary Incontinent Patients on Online Peer Support Groups-A Pilot Study

People suffering from Urinary Incontinence (UI) seek support and advice through online communities. The research team conducted a content analysis of nafc.org to investigate characteristics of information searched by users to analyze the effectiveness of this forum. Forty posts and the corresponding 249 responses were randomly selected and analyzed using a classification system derived by a research team from a nursing department in one of the universities in the southeastern region of the United States. The Linguistic Inquiry and Word Count (LIWC) generated an average tone rating of 35.21 for question posts and 53.20 for response posts. The findings highlighted the user’s need to seek advice concerning symptoms of UI resulting in 72.5% of question posts in this category and the responders need to empathize with the initial poster by sharing their own experiences resulting in 41.76% of responses in this category. We plan to continue the study with the analysis of 200 questions and their corresponding responses to better explore the emotions and needs shared in the forum.

Comparing Indicators of Suicidality Among Users in Different Types of Nonprofessional Suicide Message Boards.

Little is known about linguistic differences between nonprofessional suicide message boards that differ in regard to their predominant attitude to suicide. To compare linguistic indicators potentially related to suicidality between anti-suicide, neutral, and pro-suicide message boards, and between the types of posters (primary posters, who initiate the thread, and the respective respondents). In all, 1,200 threads from seven German-language nonprofessional suicide message boards were analyzed using the software Linguistic Inquiry and Word Count (LIWC) with regard to wording related to suicidal fantasies, aggression, and indicators of so-called suicidal constriction. Data were analyzed with ANOVA. There were fewer words related to affective, social, cognitive, and communicative processes in pro-suicide message boards than in other boards. Death-related wording and aggression as well as tentative wording appeared more prevalent in pro-suicide boards. Complex language structures cannot be analyzed with LIWC. The results suggest fewer emotion words and wording related to social circumstances among primary posters and respondents in pro-suicide boards as compared with other boards, and a higher use of death- and aggression-related words. These findings might signal a higher degree of suicidality or sheer differences in matters of interest or social desirability. The differences require attention in practice and research.

SDF: psychological Stress Detection Framework from Microblogs using Pre-defined rules and Ontologies

Spreading of Unwanted microblogs from Social Networking Sites (SNS) is pervasive in social media that leads to unaccountable disturbances such as Mental disorders, Wastage of precious time, Break-up of relationships, Stressness giving birth to psychological health problems and manymore. To overcome these problems, the immense necessity is to ignore those unwanted microblogs in SNS, which is uncontrollable by humans due to addiction towards social media. Even the literate people fall prey to psychological stress from SNS. This seriousness of stress related issues is very rarely attended by researchers, to tackle such vicious microblogs. The prediction strategy is proposed named as Stress Detection Framework (SDF) to analyze the stress in microblog. SDF is developed using Ontology based Information Extraction technique using Probabilistic Model (GSHL & TreeAlignment Algorithm ), set of pre-defined knowledge based logical rules that constitutes of low-level attributes (simple textual, linguistic words) and visual features (emoticons & Images) and social Interaction (Likes and Dislikes) to detect and predict stress in microblog messages.SDF is compared with TeniStrength that has shown an increase of 94.2% of stress detection rate. The experimental results obtained will aid to take precise decision for blocking/eradicating/ segregating stress related microblogs from Social media (especially SNS).

A combined lexical and segmental therapy approach in a participant with pure alexia

ABSTRACTBackground: Pure alexia is characterized by effortful left-to-right word processing, leading to a pathological length effect during reading aloud. Results of previous therapy outcome research suggest that patients with pure alexia tend to develop and maintain an adaptive sequential reading strategy in an effort to cope with their severe deficit and at least master a slow and laborious reading mode.Aim: We applied a theory-based, strategy-driven and eye-movement-supported therapy approach on HC, a participant with pure alexia. Our intention was to help optimizing his very persistent sequential reading strategy, while concurrently facilitating fast parallel word processing.Methods & Procedures: Therapy included a systematic combination of segmental and holistic reading as well as text reading components. Exposure duration and font size were gradually reduced. Following a single case experimental reading design with follow-up testing, we assessed reading performance at four testing points focusing on analyses of linguistic errors and word viewing patterns.Outcomes & Results: With respect to reading accuracy and oculomotor measures, the combined therapy approach resulted in sustained training effects evident in significant improvements for trained and untrained word materials. Text reading intervention only led to therapy specific improvements. Spatio-temporal analyses of eye fixation positions revealed a more and more efficient adaptive strategy to compensate for reading difficulties. However, spatial changes in fixation position were less pronounced at T4, suggesting some diminishing of success at follow-up.Conclusions: Our results underscore the need for a continuous systematic training of underlying reading strategies in pure alexia to develop and sustain more economic reading procedures.