Text Analysis Tools Research Articles

Researching L2 writers’ use of metadiscourse markers at intermediate and advanced levels

Metadiscourse markers refer to aspects of text organisation or indicate a writer's stance towards the text's content or towards the reader (Hyland, 2004:109). The CEFR (Council of Europe, 2001) indicates that one of the key areas of development anticipated between levels B2 and C1 is an increasing variety of discourse markers and growing acknowledgement of the intended audience by learners. This study represents the first large-scale project of the metadiscourse of general second language learner writing, through the analysis of 281 metadiscourse markers in 13 categories, from 900 exam scripts at CEFR B2-C2 levels. The study employed the online text analysis tool Text Inspector (Bax, 2012), in conjunction with human analysts. The findings revealed that higher level writers used fewer metadiscourse markers than lower level writers, but used a significantly wider range of 8 of the 13 classes of markers. The study also demonstrated the crucial importance of analysing not only the behaviour of whole classes of metadiscourse items but also the individual items themselves. The findings are of potential interest to those involved in the development of assessment scales at different levels of the CEFR, or to teachers interested in aiding the development of learners.

Clustering of influential wine bloggers using automated content analysis techniques

ABSTRACTThis paper considers a sample of successful wine bloggers, and clusters them into four distinct segments that could be targeted by wine marketers in different ways. Using text that they wrote in response to being named to a survey of 100 top wine blogs, we employ an advanced textual analysis tool (LIWC) to categorize the writings according to the following characteristics: analytical thinking, clout, authenticity, and emotional tone. This data is then used in a clustering procedure that distinguishes four distinct groups of bloggers: the Analysts, the Agnostics, the Authentic Pessimists, and the Confident Optimists.

Topic models meet discourse analysis: a quantitative tool for a qualitative approach

ABSTRACTQuantitative text analysis tools have become increasingly popular methods for the operationalization of various types of discourse analysis. However, their application usually remains fairly simple and superficial, and fails to exploit the resources which the digital era holds for discourse analysis to their full extent. This paper discusses the discourse-analytic potential of a more complex and advanced text analysis tool, which is already frequently employed in other approaches to textual analysis, notably topic modelling. We argue that topic modelling promises advances in areas where discourse analysis has traditionally struggled, such as scaling, repetition, and systematization, which go beyond the contributions of simpler frequency and collocation counts. At the same time, it does not violate the epistemological premises and methodological ethos of even the more radical theories of discourse, we will demonstrate. Finally, we present two small case studies to show how topic modelling – when used with appropriate parameters – can straightforwardly enhance our ability to systematically investigate and interpret discourses in large collections of text. Abbreviations: CDA: Critical Discourse Analysis; LDA: Latent Dirichlet Allocation

Representación de los actores socioculturales en las crónicas de indias de la «Conquista»

Este artículo examina la representación de los actores socioculturales en diez crónicas de Indias de la «Conquista», para mostrar la concepción y distinción entre colonizadores y colonizados en el mundo colonial. El análisis toma como base teórica y metodológica los estudios críticos del discurso (ecd), en particular el modelo de Van Leeuwen de representación de los actores sociales. Se utilizan las herramientas de análisis textual Nvivo y t-lab 7.5, que permiten realizar un examen léxico-semántico de las crónicas seleccionadas. Como resultados de la indagación, se halló que los europeos del mundo colonial se autorrepresentaban a través del uso de nombres propios, la honorificación y los títulos de oficio, mientras que los pueblos prehispánicos eran representados mediante la categorización y la asimilación. Esto implica que los primeros se describían a partir de rasgos personales, humanos y «civilizados», en cambio los segundos eran concebidos mediante abstracción, generalización y homogenización, factores que los deshumanizaban.

Analysis of the disciplines of postgraduate rehabilitation programs in Brazil

Abstract Introduction: Due to the increasing number of postgraduate programs in rehabilitation science and of masters and doctoral researchers in Brazil, there has been significant improvement in the production and quality of these studies. However, this only addresses some research fields but not others, which highlights the need to show the current professional development process and discuss the role of these professionals in an interdisciplinary framework. Objective: To analyze the research lines and disciplines of Brazilians’ postgraduate programs in rehabilitation science. Method: A qualitative descriptive study used the Sucupira platform and data sought from websites properly registered on Capes (Coordination for the Improvement of Higher Education Personnel). Data frequency analysis and the relation between research lines and disciplines were achieved using TextStat (Simple Text Analysis Tool), version 3.0. Results: The most frequent fields of study among the postgraduate programs analyzed were neurology, cardiorespiratory, and musculoskeletal. The description of the research lines and their objectives aim the assessment or intervention for rehabilitation comprehension. Conclusion: The research lines and disciplines do not follow epistemological discussions, neither the change of concepts or paradigms necessary for the successful entry of these professionals into an interdisciplinary framework.

Operationalizing “Internationalization” in the Community College Sector: Textual Analysis of Institutional Internationalization Plans

Aim/Purpose: This paper evaluates three community college internationalization plans using quantitative textual analysis to explore the different foci of institutions across three U.S. states. Background: One of the purposes of community college internationalization is to equip future generations with the skills and dispositions necessary to be successful in an increasingly globalized workforce. The extent to which international efforts have become institutionalized on a given campus may be assessed through the analysis of internationalization plans. Methodology: We use the textual analysis tool Voyant, which has rarely been employed in educational research, being more frequently applied in the humanities and under the broad heading of “digital scholarship”. Contribution: Extant literature examining internationalization plans focuses on the four-year sector, but studies centered on the two-year sector are scarce. This study addresses that gap and seeks to answer the research questions: How do community colleges operationalize internationalization in their strategic plans? What terms and/or concepts are used to indicate international efforts? Findings: Key findings of this study include an emphasis on optimization of existing resources (human, cultural, community, and financial); the need for a typology of open access institution internationalization plans; and the fragmentation of international efforts at the community college level. Impact on Society: It is clear that internationalization at community colleges may take shape based on optimization of resources, which begs the question, how can education sector actors best support open access institutions in developing plans tailored to the local context and resources at hand? Future Research: We recommend additional use of quantitative textual analysis to parse internationalization plans, and imagine that both a larger sample size and cross-national sample might yield interesting results. How do these institutional groupings operationalize internationalization in the corpus of their plans?

Building Resources For Vietnamese Clinical Text Processing

Clinical texts contain textual data recorded by doctors during medical examinations. Sentences in clinical texts are generally short, narrative, notstrictly adhering to Vietnamese grammar and contain many medical terms which are not present in general dictionaries. In this paper, we investigate the tasks oflexical analysis and phrase chunking for Vietnam eseclinical texts. Although there exist several tools for general Vietnamese text analysis, these tools showeda limited quality in the clinical domain due to the specific grammatical style of clinical texts and the lack of medical vocabulary. Our main contributions are the construction of an annotated corpus (vnEMR) and lexical resources in the medical domain and in consequence theimprovement of the quality of the tools for clinical text analysis, including word segmentation, part-of-speech tagging and chunking.

The uncertainties of enhancement: A mixed-methods study on the use of substances for cognitive enhancement and it’s unintended consequences

AimsThe use of substances for cognitive enhancement has become a relatively well-studied phenomenon in recent years. However, few studies deal with the negative and unintended consequences of such practices. This article uses two data sets to explore and discuss the doubt and negative consequences that affect people using substances in the pursuit of enhancing cognition. MethodsData for the study are drawn from an online discussion forum on substances for enhancement and from ethnographic fieldwork carried out among university students in New York City. Taking a quali-quantitative approach, we combine digital text analytic tools with qualitative analysis and readings. FindingsUsing prescription stimulants and other substances for cognitive enhancement generates considerable uncertainty in terms of unclear effects, varying practices and ambivalent ethics. While the negative effects are not something easily discussed in person, references to them are very common in the online discussion forum. ConclusionsPeople who use substances for enhancement have developed a ‘folk pharmacology’ that seems to play an important role in how they perceive the negative effects. This may make people who engage in these kinds of enhancement practices less able to make informed choices about their use of these substances.

Monetary policy on twitter and asset prices: Evidence from computational text analysis

In this paper, we dissect the Twitter debate about the future course of monetary policy and trace the effects of selected topics of this discourse on U.S. asset prices. We focus on the “taper tantrum” episode in 2013, a period with large revisions in expectations about future Fed policy. Based on a novel data set of 90,000 Twitter messages (“tweets”) covering the debate of Fed tapering on Twitter, we use Latent Dirichlet Allocation, a computational text analysis tool, to quantify the content of the discussion. Several estimated topic frequencies are then included in a VAR model to estimate the effects of topic shocks on asset prices. We find that the discussion about Fed policy on social media contains price-relevant information. Shocks to the discussion about the timing of the tapering, about the broader economic policy context and worrying investors are shown to lead to significant asset price changes. We also show that the effects are mostly due to changes in the term premium of yields consistent with the portfolio balance channel of unconventional monetary policy.

Conversational Time Travel: Evidence of a Retrospective Bias in Real Life Conversations.

We examined mental time travel reflected onto individuals’ utterances in real-life conversations using a naturalistic observation method: Electronically Activated Recorder (EAR, a portable audio recorder that periodically and unobtrusively records snippets of ambient sounds and speech). We introduced the term conversational time travel and examined, for the first time, how much individuals talked about their personal past versus personal future in real life. Study 1 included 9,010 sound files collected from 51 American adults who carried the EAR over 1 weekend and were recorded every 9 min for 50 s. Study 2 included 23,103 sound files from 33 young and 48 healthy older adults from Switzerland who carried the EAR for 4 days (2 weekdays and 1 weekend, counterbalanced). 30-s recordings occurred randomly throughout the day. We developed a new coding scheme for conversational time travel: We listened to all sound files and coded each file for whether the participant was talking or not. Those sound files that included participant speech were also coded in terms of their temporal focus (e.g., past, future, present, time-independent) and autobiographical nature (i.e., about the self, about others). We, first, validated our coding scheme using the text analysis tool, Linguistic Inquiry and Word Count. Next, we compared the percentages of past- and future-oriented utterances about the self (to tap onto conversational time travel). Results were consistent across all samples and showed that participants talked about their personal past two to three times as much as their personal future (i.e., retrospective bias). This is in contrast to research showing a prospective bias in thinking behavior, based on self-report and experience-sampling methods. Findings are discussed in relation to the social functions of recalling the personal past (e.g., sharing memories to bond with others, to update each other, to teach, to give advice) and to the directive functions of future-oriented thought (e.g., planning, decision making, goal setting that are more likely to happen privately in the mind). In sum, the retrospective bias in conversational time travel seems to be a functional and universal phenomenon across persons and across real-life situations.

The Tool for the Automatic Analysis of Cohesion 2.0: Integrating semantic similarity and text overlap.

This article introduces the second version of the Tool for the Automatic Analysis of Cohesion (TAACO 2.0). Like its predecessor, TAACO 2.0 is a freely available text analysis tool that works on the Windows, Mac, and Linux operating systems; is housed on a user's hard drive; is easy to use; and allows for batch processing of text files. TAACO 2.0 includes all the original indices reported for TAACO 1.0, but it adds a number of new indices related to local and global cohesion at the semantic level, reported by latent semantic analysis, latent Dirichlet allocation, and word2vec. The tool also includes a source overlap feature, which calculates lexical and semantic overlap between a source and a response text (i.e., cohesion between the two texts based measures of text relatedness). In the first study in this article, we examined the effects that cohesion features, prompt, essay elaboration, and enhanced cohesion had on expert ratings of text coherence, finding that global semantic similarity as reported by word2vec was an important predictor of coherence ratings. A second study was conducted to examine the source and response indices. In this study we examined whether source overlap between the speaking samples found in the TOEFL-iBT integrated speaking tasks and the responses produced by test-takers was predictive of human ratings of speaking proficiency. The results indicated that the percentage of keywords found in both the source and response and the similarity between the source document and the response, as reported by word2vec, were significant predictors of speaking quality. Combined, these findings help validate the new indices reported for TAACO 2.0.

A Comparison of Readability and Understandability in Second Language Acquisition Textbooks for Pre-service EFL Teachers

Teachers must be able to comprehend their textbooks in order to fully benefit from their preparation programs. However, it is yet unclear whether textbooks used to teach challenging content to pre-service non-native speaking English teachers might be beyond their ability. To investigate this question, a textbook readability analysis was performed with the Coh-Metrix text analysis tool. Textbook understandability was also assessed by means of maze passages given to teacher candidates in a pre-service English teacher education program. Readability analyses results indicated that the majority of the texts are excessively challenging for L2 readers at the level of the participants. Understandability findings revealed that many texts were able to be read independently but that all texts could be understood with scaffolding. Contrary to prior understandability research findings that showed that these textbooks were too difficult, this study found them to be suitable for their audience. However, a correlation between text understandability and course grades indicates that ability to comprehend the text could relate to course performance. Implications are that EFL teacher educators must recognize the importance of readability for textbook selection criteria and provide learners with access to other supplementary materials to scaffold their learning.

Beyond subjective judgments: Predicting evaluations of creative writing from computational linguistic features

The question of how to evaluate creativity in the context of creative writing has been a subject of ongoing discussion. A key question is whether something as elusive as creativity can be evaluated in a systematic way that goes beyond subjective judgments. To answer this question, we tested whether human evaluations of the creativity of short stories can be predicted by: (1) established measures of creativity and (2) computerized linguistic analyses of the stories. We conducted two studies, in which college students (with and without interest and experience in creative writing) wrote short stories based on a writing prompt. Independent raters (six in Study 1, five in Study 2) assessed the stories using an evaluation rubric specifically designed to assess aspects of creativity, on which they showed high interrater reliability. We provide evidence of convergent validity, in that the rubric evaluations correlated with established creativity measures, including measures of divergent thinking, associative fluency, and self-reported creative behavior and achievements. Linguistic properties of the short stories were analyzed with two computerized text analysis tools: Coh-Metrix, which analyzes aspects of text cohesion and readability, and Linguistic Inquiry and Word Count, which identifies meaningful psychological categories of the text content. Linguistic features predicted the human ratings of creativity to a significant degree. These results provide novel evidence that creative writing can be evaluated reliably and in a systematic way that captures objective features of the text. The results further establish our evaluation rubric as a useful tool to assess creative writing.

What You Say Your Strategy Is and Why It Matters: Natural Language Processing of Unstructured Text

This study explores how new text analysis tools can be used in strategic management research that examines unstructured textual data. We build on two established natural language processing (NLP) t...

What's the Story? A New Perspective on the Value of Economic Forecasts

We apply textual analysis tools to measure the degree of optimism versus pessimism of the text that describes Federal Reserve Board forecasts published in the Greenbook. The resulting measure of Greenbook text sentiment, “Tonality,” is found to be strongly correlated, in the intuitive direction, with the Greenbook point forecast for key economic variables such as unemployment and inflation. We then examine whether Tonality has incremental power for predicting unemployment, GDP growth, and inflation up to four quarters ahead. We find it to have significant and substantive predictive power for both GDP growth and unemployment, particularly since 1991: higher (more optimistic) Tonality presages higher GDP growth and lower unemployment, relative to the Greenbook point forecasts. We then test whether Tonality helps predict monetary policy and stock returns. Higher Tonality has some power to predict tighter than forecasted monetary policy, while it has substantial power for predicting higher 3-month, 6-month, and 12-month stock market returns.

Beyond Words of Popularization Mining Reviews on Comic Books Movies

Objectives: This paper aims to analyse the terms used by the of movie critics on popular comic book movies. From the analysis we are able to know what are the factors that most movie critics will focus at, whether the top movie critics review has an impact on the decision of general movie goers and from this will determine why the movies was a box office success. Methods: The research is done via text mining from SAS Enterprise Miner software which utilize the text analytics tool to analyse movie reviews by movie critics’ professionals. The analytical processes involved are text parsing, text filtering, text clustering and the text topic method. Correlation of terms is identified to help in determining the significance of each terms nested within the reviews. Findings: The findings show that the actors, the movie's characters and the film storyline are the most common type of terms that most movie critics are focusing on, thus this factors is what drives the reputation of the film and making it a blockbuster hit around the world. Application/Improvements: The results obtained can help the entertainment industry on their decision making on what to focus on when it comes to producing comic books superheroes into movies based on the sentiment analysis in identifying the postive and negative terms and their relationship with one another.

Исследовательский проект как инструмент обучения методам анализа текста: предсказание класса поста в социальной сети

The article describes a student research project on predicting the class of a post on a social network based on its textual content. The features of the project are discussed as an integral part of the trajectory of teaching data analysis methods, including text analysis methods and tools that are often not included in machine learning courses. The formulation of the problem, the stages of its solution, the sequence of considering new methods as a way for solving students’ problems, as well as the used tool of the R environment are described. The possibilities of expanding the task and its modifications depending on the level of training of students are given.

Measuring Query Complexity in Web-Scale Discovery: A Comparison between Two Academic Libraries

This study reports on the examination of search transaction logs from web-scale discovery tools at two Indiana University campuses. The authors discuss how they gathered search queries from transaction logs, categorized queries according to the Library of Congress Classification schedule, and then examined queries using text analysis tools in order to identify which subjects were being searched and whether users were using advanced search options. The results of this investigation demonstrate how transaction logs may be used to communicate user interactions within discovery services. The findings offer detailed insight into the subjects and skills that teaching faculty and librarians should communicate to improve information literacy instruction. The search queries also uncover information needs that provide direction for collection managers.

Gender Differences in the Use of Pronouns in Asynchronous Computer-Mediated Communication

This paper analyses gender differences in the use of pronouns by men and women bloggers of five leading Pakistani English e-newspaper blogs. For this purpose, 11258 blog posts from 1674 men and 1212 women bloggers were collected and two gendered corpora, comprising around nine million tokens (men=5.6 million; women=3.3 million), were built and subjected to analysis with the help of two automated text analysis tools: Linguistics Inquiry and Word Count 2015 and AntConc 3.4.4. Preliminary results, so obtained, were further worked out for descriptive and inferential statistics with XLSTAT and MS Excel. The results show that preference for pronouns is a gender marker in a text while results for particular pronouns vary. The examination of frequencies, concordances and collocates of various pronouns also revealed some other similarities, differences and cultural nuances in gendered language. Keywords: Language and Gender, Computer Mediated Communication, Pakistani English E-Newspaper

Bridging Text Visualization and Mining: A Task-Driven Survey.

Visual text analytics has recently emerged as one of the most prominent topics in both academic research and the commercial world. To provide an overview of the relevant techniques and analysis tasks, as well as the relationships between them, we comprehensively analyzed 263 visualization papers and 4,346 mining papers published between 1992-2017 in two fields: visualization and text mining. From the analysis, we derived around 300 concepts (visualization techniques, mining techniques, and analysis tasks) and built a taxonomy for each type of concept. The co-occurrence relationships between the concepts were also extracted. Our research can be used as a stepping-stone for other researchers to 1) understand a common set of concepts used in this research topic; 2) facilitate the exploration of the relationships between visualization techniques, mining techniques, and analysis tasks; 3) understand the current practice in developing visual text analytics tools; 4) seek potential research opportunities by narrowing the gulf between visualization and mining techniques based on the analysis tasks; and 5) analyze other interdisciplinary research areas in a similar way. We have also contributed a web-based visualization tool for analyzing and understanding research trends and opportunities in visual text analytics.