Computerized Text Analysis Research Articles

Can climate-related information disclosures strengthen green innovation capacity? Firm-level evidence using textual analysis

This study presents novel insights on modelling the implications of voluntary climate-related information disclosure on corporate green innovation (GI) in China. Based on a constructed dataset of 13,664 firm-year observations between 2014 and 2020, we quantify climate-related disclosures under the Task Force on Climate-Related Financial Disclosures framework using computerized text analysis. Our findings show that climate-related information disclosure substantially bolsters corporate green innovation after addressing endogeneity concerns. However, the promoting effects vary drastically across industry attributes, ownership structure, and environmental regulations. Further channel analysis demonstrates that “greenwashing” behaviours and financial constraints adversely moderate the nexus between climate-related information disclosure and green innovation of firms, while digital finance positively moderates it. Overall, this study enriches the literature and offers practical implications for firms engaging in the green innovation process more effectively under a more transparent environment-related disclosure system.

Mindsets of suicide trajectories: An Linguistic Inquiry and Word Count analysis of suicide hotline conversations.

The aim of the study was to explore the psychological characteristics of the individuals with various suicide risks using computerized text analysis, in the hopes of a better understanding of suicide trajectories. 627 first-time callers' records were randomly selected from Taiwan An-Shin Hotline database between 2013 and 2018. The voice records were evaluated by two psychologists to determine the levels of suicide risk (156 with uncertainty of risk, 177 with low suicidal ideation, 157 with high suicidal ideation, and 137 with suicide preparation/attempt) and transcribed into text. The Linguistic Inquiry and Word Count 2015 (LIWC2015) program combined with Chinese dictionary were then used to calculate the frequency of word categories. Exploratory factor analysis identified four mindsets of language characteristics, named "opposition and questioning", "active engagement", "negative rumination", and "focus on death". Psychological descriptions of the mindsets were also obtained through correlation analysis with the LIWC2015 categories and indicators. The four mindsets effectively distinguished the callers with different levels of suicide risk. The psychological characteristics of people with various suicide risks can be described and differentiated via the closed-word categories and composite indicators. These results provide useful information for practitioners and researchers.

When I am sixty-four… evaluating language markers of well-being in healthy aging narratives.

Natural language use is a promising candidate for the development of innovative measures of well-being to complement self-report measures. The type of words individuals use can reveal important psychological processes that underlie well-being across the lifespan. In this preregistered, cross-sectional study, we propose a conceptual model of language markers of well-being and use written narratives about healthy aging (N = 701) and computerized text analysis (LIWC) to empirically validate the model. As hypothesized, we identified a model with three groups of language markers (reflecting affective, evaluative, and social processes). Initial validation with established self-report scales (N = 30 subscales) showed that these language markers reliably predict core components of well-being and underlying processes. Our results support the concurrent validity of the conceptual language model and allude to the added benefits of language-based measures, which are thought to reflect less conscious processes of well-being. Future research is needed to continue validating language markers of well-being across the lifespan in a theoretically informed and contextualized way, which will lay the foundation for inferring people's well-being from their natural language use.

Feelings in words: Emotion word use and cardiovascular reactivity in marital interactions.

Putting feelings into words is often thought to be beneficial. Few studies, however, have examined associations between natural emotion word use and cardiovascular reactivity. This laboratory-based study examined emotion word use (i.e., from computerized text analysis) and cardiovascular reactivity (i.e., interbeat interval changes from baseline) across two interaction contexts (i.e., conflict and positive conversations) in 49 mixed-sex married couples (age: M = 43.11, SD = 9.20) from diverse socioeconomic backgrounds. We focused on both frequency (i.e., relative proportion of emotion words) and diversity (i.e., relative proportion of unique emotion words) of emotion words. Data were collected between 2015 and 2017 and analyzed treating both partners and conversations as repeated measures, resulting in 196 observations overall (four per dyad). Findings showed that (a) when spouses used more negative emotion words (especially anger), they showed higher cardiovascular reactivity. This finding was robust when controlling for covariates; generalized across gender, interaction contexts, and socioeconomic status. Moreover, (b) when spouses used a more diverse negative emotion vocabulary, they showed higher cardiovascular reactivity, but this was not robust when controlling for negative emotion word frequency. Associations between (c) positive emotion word use and cardiovascular reactivity were not statistically significant. Verbalizing negative emotions thus seems to go along with higher cardiovascular reactivity, at least in the short term. Replication is needed across other relationship types, genders, and sexual orientations. These findings highlight emotion word use as an indicator of cardiovascular reactivity, which has implications for the identification of potential health risks that emerge during marital interactions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Linguistic markers for major depressive disorder: a cross-sectional study using an automated procedure.

The identification of language markers, referring to both form and content, for common mental health disorders such as major depressive disorder (MDD), can facilitate the development of innovative tools for early recognition and prevention. However, studies in this direction are only at the beginning and are difficult to implement due to linguistic variability and the influence of cultural contexts. This study aims to identify language markers specific to MDD through an automated analysis process based on RO-2015 LIWC (Linguistic Inquiry and Word Count). A sample of 62 medicated patients with MDD and a sample of 43 controls were assessed. Each participant provided language samples that described something that was pleasant for them. (1) Screening tests for MDD (MADRS and DASS-21); (2) Ro-LIWC2015 - Linguistic Inquiry and Word Count - a computerized text analysis software, validated for Romanian Language, that analyzes morphology, syntax and semantics of word use. Depressive patients use different approaches in sentence structure, and communicate in short sentences. This requires multiple use of the punctuation mark period, which implicitly requires directive communication, limited in exchange of ideas. Also, participants from the sample with depression mostly use impersonal pronouns, first person pronoun in plural form - not singular, a limited number of prepositions and an increased number of conjunctions, auxiliary verbs, negations, verbs in the past tense, and much less in the present tense, increased use of words expressing negative affects, anxiety, with limited use of words indicating positive affects. The favorite topics of interest of patients with depression are leisure, time and money. Depressive patients use a significantly different language pattern than people without mood or behavioral disorders, both in form and content. These differences are sometimes associated with years of education and sex, and might also be explained by cultural differences.

Non-Take-Up of Benefits and Rights: The Universality-Selectivity Debate as Reflected in Online Information and User Patterns

The present study adds valuable perspective to the ongoing theoretical and practical universality-selectivity debate in the context of (non-) take-up of benefits by delving into the online information angle. People with a digital divide may be affected by such differences since they are more likely to need selective benefits. Almost all researchers agree that knowledge is a crucial barrier to benefits take-up. However, most researchers place the information barrier at the client level and do not examine factors contributing to information incomprehensibility. Is the effectiveness of universality- or selectivity-based welfare policies reflected in the online information? Our study examined this question by a computerized text analysis of 2662 online information pages in “Kol Zchut,” a primary Israeli information website about benefits and rights, and its Google Analytics usage pattern data. The results indicated weak but significant differences between universal and selective information pages. Information complexity was higher in selective information pages. The findings were more complicated regarding usage patterns. In order to understand more deeply the information side of rights take-up, future research is needed.

Standing head and shoulders above others? Complementor experience-based design and crowdfunding success on digital platforms

The proliferation and development of crowdfunding platforms have gradually enabled a disruptive way to finance new ventures through their use. Employing an integrated empirical approach and computerized text analysis, this study aims to investigate how the configuration of multiple complementor experience-based design features affects a complementor’s engagement on crowdfunding platforms. The results indicate that content entrainment, interactive engagement and social connectivity improve crowdfunding success on digital platforms. Moreover, by further refining the linguistic and psychological components, we discover that introducing function words, designing specific content related to clout, authenticity, leisure, religion and biological process, and improving word tone also enhance project funding ratio. Using these findings as a guide, we provide a series of recommendations for fundraisers to better present their crowdfunding projects by employing complementor experience-based designs on crowdfunding platforms.

The influence of lazy information disclosure on stock price crash risk: Empirical evidence from China.

Information disclosure is an important way for investors to obtain information, the annual report text carries a lot of information, lazy information disclosure is an important form of information disclosure of the annual report text. This paper takes China's A-share listed companies from 2011 to 2022 as the research sample, takes the annual report text information disclosure form as the entry point, uses the computer text analysis technology to measure the text similarity of the annual report to measure the lazy information disclosure, and explores its impact on stock price crash risk. The results show that there is a positive correlation between the similarity of annual report text and the risk of stock price crash, that is, when the information of annual report text is presented in the form of lazy information disclosure, the risk of stock price crash increases. For companies audited by key auditing institutions, the positive correlation between the similarity of their annual reports and the risk of stock price crash is not significant, indicating that key auditing institutions will weaken the positive correlation between lazy information disclosure and the risk of stock price crash. Further, through external attention and analysis of the time delay of annual report disclosure, it is concluded that the management lacks the opportunity and time to hide the bad news, so it is clear that the lazy information disclosure comes from the business situation "the fact is so". The research conclusion of this paper provides evidence support for the influence of lazy information disclosure on stock price crash risk, and also provides useful reference for regulators to improve information disclosure policies and effectively prevents and resolves stock price crash risk.

Observer-based and computerized measures of the patient’s mentalization in psychotherapy: A scoping review

Objective In recent decades, mentalizing has found its permanent place both in therapeutic practice and in psychotherapy research. Inconsistent results and null results are often found. Therefore, the different methodological approaches should be examined in more detail. A scoping review was conducted to provide an overview of the approaches that measure the patient's mentalizing ability based on therapy sessions or in the course of psychotherapy. Method For the scoping review, a literature search was conducted in four databases. A total of 3217 records were identified. Results We included 84 publications from 43 independent studies. Most studies used the Reflective Functioning Scale and applied the scale to therapy sessions or the Adult Attachment Interview. The other identified approaches used a computerized text analysis measure or clinician-report measures. Mostly good psychometric properties of the measures were reported. The Reflective Functioning Scale applied to the Adult Attachment Interview was the only measure that proved to be sensitive to change. Conclusion More economical variants to the time-consuming Reflective Functioning Scale applied to the Adult Attachment Interview are being developed continuously. In some cases, there is no standardized approach, or the measures are used only sporadically and require further and more comprehensive psychometric evaluations.

Layering Ideologies from Deng Xiaoping to Xi Jinping: Tracing Ideological Changes of the Communist Party of China Using Text Analysis

This article argues that ideological changes of the Communist Party of China follow a layering model, whereby a new discourse developed by each top leader adds a fresh layer to the existing ideological system. Computerised text analysis of college materials for ideology courses from 1978 to 2018 lends support to this model, quantifying the changes over time in the prevalence of each layer in the Party’s ideology. Marxism, Maoism and Dengism have remained as the foundational and dominant components of the ideological system, even during the ascent of Xi Jinping Thought and nationalistic narratives.

Rearranging the News Agenda: State Action and News Media Reporting on Violence Against Women in Brazil

In this article, I examine the factors that influence the amount and content of news media reporting on violence against women (VAW) in Brazil. VAW was not considered a relevant political problem until very recently when states began to respond to feminist demands by adopting policies to criminalize VAW and providing resources to survivors. I theorize that the process of improving state action on VAW increases news media attention to these stories. I also argue that heightened political attention to VAW increases news media discussion of policies and laws addressing VAW. Employing time series analysis and computer text analysis of an original dataset from Brazil (2004–2019), I find that strong legislation and congressional bill introduction exert significant positive effects on news media reporting of VAW.

The writing is on the wall: predicting customers' evaluation of customer-firm interactions using computerized text analysis

PurposeThis methodological paper demonstrates how service firms can use digital technologies to quantify and predict customer evaluations of their interactions with the firm using unstructured, qualitative data. To harness the power of unstructured data and enhance the customer-firm relationship, the use of computerized text analysis is proposed.Design/methodology/approachThree empirical studies were conducted to exemplify the use of the computerized text analysis tool. A secondary data analysis of online customer reviews (n = 2,878) in a service industry was used. LIWC was used to conduct the text analysis, and thereafter SPSS was used to examine the predictive capability of the model for the evaluation of customer-firm interactions.FindingsA lexical analysis of online customer reviews was able to predict evaluations of customer-firm interactions across the three empirical studies. The authenticity and emotional tone present in the reviews served as the best predictors of customer evaluations of their service interactions with the firm.Practical implicationsComputerized text analysis is an inexpensive digital tool which, to date, has been sparsely used to analyze customer-firm interactions based on customers' online reviews. From a methodological perspective, the use of this tool to gain insights from unstructured data provides the ability to gain an understanding of customers' real-time evaluations of their service interactions with a firm without collecting primary data.Originality/valueThis research contributes to the growing body of knowledge regarding the use of computerized lexical analysis to assess unstructured, online customer reviews to predict customers' evaluations of a service interaction. The results offer service firms an inexpensive and user-friendly methodology to assess real-time, readily available reviews, complementing traditional customer research. A tool has been used to transform unstructured data into a numerical format, quantifying customer evaluations of service interactions.

Gender Differences in Letters of Recommendation for Gynecology Surgical Fellowship Applicants: Analysis of One Program's Recruitment Cycle

To evaluate if there are gender differences in the letters of recommendation (LOR) written for residents applying to gynecology surgical fellowships. Retrospective study. Single, academic institution. LOR for applicants to gynecology oncology, urogynecology, and minimally invasive gynecology fellowships during the 2019-2020 application cycle. Not applicable. We analyzed the linguistic content of the letters for the presence of 4 summary variables and 21-word categories based on previous studies using a validated computerized text analysis software. We used multivariable analysis using linear mixed models to compare letter linguistic characteristics by applicant gender. We performed qualitative content on letters and compared the frequency of code themes by gender. The mixed-method design was planned to analyze domains not captured in text analysis. Among 680 letters written for 186 applicants, 124(18.2%) were written for men and 556 (81.8%) were written for women. There were no differences in the least square mean (SE) word counts for LOR written for men and women applicants, 465(20.0) v. 458(9.4) words, p=.74. On multivariable analysis, LOR written for men had higher authentic tone and more risk words (p=.005 and p=.03, respectively). LOR written for women contained more communal (relationship-oriented) words (p=.006). The qualitative analysis demonstrated ability, interpersonal traits, surgical skills, and research were the most mentioned themes. Comments about compassion/empathy, leadership potential, teaching, interpersonal skills, and patient rapport were found more in letters for men. More doubt raisers (words that raise doubt or concern) were present in letters for men, but letters for both genders had similar levels of negative criticism. In contrast, comments on ability, being "drama-free", and self-awareness were found more in letters for women. There were gender differences in LOR written for obstetrics and gynecology surgical sub-specialty fellowship applicants indicating presence of gender bias.

Language and gender: Computerized text analyses predict gender ratios from organizational descriptions.

Previous research has shown that language in job adverts implicitly communicates gender stereotypes, which, in turn, influence employees' perceived fit with the job. In this way, language both reflects and maintains a gender segregated job market. The aim of this study was to test whether, and how, language in organizational descriptions reflects gender segregation in the organizations by the use of computational text analyses. We analyzed large Swedish companies' organizational descriptions from LinkedIn (N = 409), testing whether the language in the organizational descriptions is associated with the organizations' employee gender ratio, and how organizational descriptions for organizations with a majority of women and men employees differ. The statistical analyses showed that language in the organizational descriptions predicted the employee gender ratio in organizations well. Word clouds depicting words that differentiate between organizations with a majority of women and men employees showed that the language of organizations with a higher percentage of women employees was characterized by a local focus and emphasis on within-organizations relations, whereas the language of organizations with a higher percentage of men employees was characterized by an international focus and emphasis on sales and customer relations. These results imply that the language in organizational descriptions reflects gender segregation and stereotypes that women are associated with local and men with global workplaces. As language communicates subtle signals in regards to what potential candidate is most sought after in recruitment situations, differences in organizational descriptions can hinder underrepresented gender groups to apply to these jobs. As a consequence, such practices may contribute to gender segregation on the job market.

Content Analysis of Problem-Based Learning on Engineering Students’ Unemployment Awareness

Qualitative content analysis can be applied to analysing textual words written in different types of reflection assignments. Thus, the aim of this research is to investigate the adoption of problem-based learning (PBL) learning to understanding the knowledge and level of awareness of chemical engineering students regarding graduate unemployment in Malaysia. Participants are 88 second-year students enrolled on the Differential Equation course at the National University of Malaysia. With technological breakthroughs in computerised text analysis that enable researchers to collect and analyse large amounts of textual data, content analysis employing an inductive approach is used to analyse students’ PBL reflective writing which expresses whether all the main factors of graduate unemployment can be identified. The result reveals that almost 80% of participants were unable to meet the requirement of the first stage of PBL, which is to identify the critical learning issue i.e., unemployment factors. This group of students only managed to identify person-related factors associated to unemployment: working experience and soft skills. Only 15 participants, however, have successfully identified all six factors influencing graduate employability. Practical learning, entrepreneurial skills, internal audit and basic qualifications of graduates, along with soft skills and working experience are the main components of the higher education curriculum that have a significant impact on the unemployment problem of graduates in Malaysia if they are revised. The findings have important implications for how the institution can properly plan and take appropriate actions to raise unemployment awareness among students at an early stage of their study.

Putting on the Blitz: Urgency and Department of Defense Communications in Times of Budget Shortfall

The existing theories of interaction between Congress and the Department of Defense (DOD) focus on elite-level principle-actor problems. However, the Department, as one of the most popular institutions in the United States, also has significant public appeal and maintains an active public affairs arm. This article builds on theories of bureaucratic reputation to argue that the DOD uses its public communications to advocate for its own budget. I leverage computerized text analysis to examine over 40,000 public facing documents published by the DOD since 2005. I find evidence that the DOD changed both the timing and the content of its public-facing communications to strategically argue for its budget. This is true during large budgetary shifts (like the U.S. budget sequester) and during the period of the year that the budget is under debate.

Language as an interpersonal marker in English dissertation acknowledgments

Expressing gratitude and patronage in the form of dedication or acknowledgment can be traced back to the 16th century (Görlach, 2004). In the present time, writing an acknowledgment section has become a common practice in scholarly works, such as books, dissertations, theses, and journal articles. Research on acknowledgments as a text type, however, is relatively new. In his pioneering work, Hyland (2003) dubbed dissertation acknowledgments ‘a Cinderella genre’ because it is often regarded as a taken-for-granted component in a dissertation and has not received due academic attention. Unlike other conventional academic genres that aim to establish claims and reputation, dissertation acknowledgments reflect the reciprocal gift-giving among scholars, constituting ‘the most explicitly interpersonal genre of the academy’ (Hyland, 2004: 323). In addition to expressing gratitude to others, writers also use the acknowledgments section to build interpersonal relationships with their academic colleagues and/or professional communities (Chan, 2015). In this study, we adopt computerized text analysis to further explore how language patterns mark the interpersonal features in English dissertation acknowledgments.

When Groups of Different Sizes Collide: Effects of Targeted Verbal Aggression on Intragroup Functioning

When competing for scarce resources, groups can behave aggressively toward one another. Realistic conflict theory suggests that intergroup hostility internally ties groups together, thus improving intragroup functioning. In contrast, conflict spillover theory suggests that aggressive behaviors between groups can permeate to the intragroup level and thus worsen intragroup functioning. We reconcile these two opposite perspectives by introducing the relative group size as a moderator that determines when and how targeted verbal aggression from one group harms or improves intragroup functioning in the targeted group. We tested our hypotheses using a sample of in-situ observations of transcribed plenary discussions in the German national parliament and compared intergroup targeted verbal aggression by distinguishing targeted verbal aggression from two social groups (i.e., a new populist smaller party vs. a larger group of veteran parliament members). We measured targeted verbal aggression as a form of hostile intergroup behavior from each social group using computerized text analyses. We analyzed intragroup functioning using a measure of verbal mimicry. Our results show support for our hypotheses. We discuss theoretical and practical implications for the verbal aggression and intergroup relations literature.

Did destructive leadership help create the conditions for the spread of Covid-19, and what are the early warning signs?

This research asks: ‘were there any objectively identifiable signals in the words leaders used in the early stages of the Covid-19 pandemic that can be associated with ineffective management of the crisis?’ We chose to focus on the leaders of the two English-speaking nations that fared worst and best in the pandemic, the United States and New Zealand. By way of background and in order to contextualise the research, we compared and contrasted Trump’s and Ardern’s leaderships using the toxic triangle framework of destructive leadership. We then focused on the leader behaviour element of the triangle by using computerised text analysis (CTA) to analyse Trump’s and Ardern’s public pronouncements during the critical early stages of the pandemic. Based on a similarity index (S), we identified linguistic markers associated with destructive leader behaviours and negative outcomes (Trump) and non-destructive leader behaviours and positive outcomes (Ardern). We discuss future applications of these linguistic markers for the diagnosis both of incumbent and potential leaders’ responses to crises management.

When I'm“Good＂, You Should Watch Out: Computerized Text Analysis of Linguistic Trajectory of Sexual Re-Offense

在臺灣現行制度下，性侵害加害者一旦離開監獄就必須進入社區治療，然而隨著性罪犯追蹤監控的期程拉長，其再犯率也隨之上升，也就顯示日常生活流轉匯聚各式各樣的境遇，進而影響性再犯的危險因子，然在性罪犯社區處遇歷程中如何評估性犯罪者的再犯企圖一直是臨床實務上值得關注的問題。本個案報告嘗試分析隨時間軌跡的滾動，如何由性犯罪者之日常語言使用找出反映個人內在心理狀態之線索，藉此觀察性侵害加害者之語言徵兆變化情形與再犯之關聯。本個案報告藉由分析一名資料庫匯出之性侵害加害人於社區治療期間所書寫之雙週誌，連續紀錄將近一年直至其再犯性犯罪，共21篇記載其社區治療參與個人生活狀況之自由書寫，將相關內容透過「語文探索與字詞計算」（LIWC）軟體進行五項具有心理意義之文字變項的電腦化文本分析。研究結果發現語言風格透過長時間紀錄後可以觀察到該性犯罪者之再犯可能徵兆，特別是在總字詞數由多到少之變化、正負向情緒詞彙相反的變動態勢，以及誠實性指標呈現V型變化上，符合Ekman、Vrij、DePaulo等三研究團隊有關欺瞞理論之推衍，也因此本研究認為具有心理意義之文字變項可反映潛藏犯罪意圖的細微變化，而與後續再犯結果有關，亦可作為性犯罪者心理評估之參考指標，值得未來透過性犯罪者之大樣本數據分析加以檢證。According to the current legal system in Taiwan, sex offenders must enter a community intervention program after being released from prison. However, recent research of sex offenders has suggested that over the longer term after offenders are released, they have a high rate of sexual re-offense. This shows that the daily struggles while returning to society might contribute to sexual re-offense in different ways, so as to impact the risk factor of sexual re-offense. Thus, assessing the re-offense attempts of sex offenders in the community intervention program is worthy of attention in clinical practice. However, considering the importance of monitoring linguistic behaviors, there is very little existing research that has empirically documented the language use of sex offenders and how that may impact recidivism of sexual offense. Therefore, the aim of this case report attempts to explore how sex offenders' state of minds are reflected in daily language use and how linguistic markers and sexual re-offense may be related. Pennebaker and his colleagues have provided excellent reviews of the psychological aspect in language use. They believe that either expressive writing or spoken language demonstrate cognitive reflective models. Instead of focusing on ＂what＂ is said by the individuals, paying attention to ＂how＂ the individuals say it is much more crucial. Furthermore, it opened a window for researchers to analyze the psychological vulnerabilities or risks of sex offenders as well as having further understanding of the underlining altered state of mind that is intertwined with the surroundings. Considering these concerns, this case study involved a biweekly log written by an ex-sex offender in a community intervention program. The time frame for the study lasted nearly one year until the re-offense occurred. A total of twenty-one free-writing diaries were analyzed with a computerized text analysis software, Linguistic Inquiry and Word Count (LIWC). Beyond examining several categories of words with psychological meanings, such as negative and positive affect, this case study also applies higher-order algorithms based on LIWC dictionaries, including the index of complex thinking, the index of honesty, and the index of social-emotional style. Considering months as the analysis unit, the one-year period is divided into the initial stage (April to July), incubation stage (August to December) and action stage (January to March). The results suggested that the language style could possibly indicate signs of recidivism for sex offenders over the long-term while recording their thoughts. The language used during the action stage demonstrated four valuable language shifts compared to other stages. First, the total number of words continually decreased over time. Second, positive affect words decreased and negative affect words increased. Third, the index of complex thinking decreased. Fourth, the index of honesty rose with a V-shape. This result is aligned with the inference of the deception theory of Ekman, Vrij, and DePaulo. To conclude, the study may be of importance in explaining language with psychological meaning that could reflect subtle changes in hidden intention of crimes. In addition, the findings of the study also have implications for observing signs of deception and the subsequent re-offense from the written text. Thus, language analysis is proving to be a useful source for conducting psychological evaluation and risk management for sex offenders who under treatment. That said, the generalization of the results to other populations with different backgrounds may be limited, so more research is called for to expand the understanding of the language style of sex offenders.