Expressions of doubt and trust in online user reviews

Online User Reviews ◽

How do expressions of doubt affect trust in online reviews? Previous research leads to conflicting predictions: some studies find that people trust confident advisors more than doubtful advisors, whereas others find doubtful advisors are trusted more, especially when advisors have salient conflicts-of-interest. We tested the effects of doubt in the Yelp Open Dataset (N = 5.9 million user reviews). Reviews were coded using the Linguistic Inquiry Word Count (LIWC) software, which contains two dictionaries related to doubt, tentativeness and (lack of) certainty. Doubtful reviews were more likely to be seen as useful, and this result was robust when controlling for other psychological variables, as well as review length and linguistic complexity. The beneficial consequences of expressing doubt were strongest for positive (5-star) reviews, suggesting that doubt may mitigate concerns about the veracity of overly positive reviews. The present study emphasizes the advantages of expressing doubt.

Examining Users’ Concerns while Using Mobile Learning Apps

International Journal of Interactive Mobile Technologies (iJIM) ◽

10.3991/ijim.v15i15.22345 ◽

2021 ◽

Vol 15 (15) ◽

pp. 47

Author(s):

Senanu Okuboyejo ◽

Ooreofe Koyejo

Keyword(s):

Mobile Learning ◽

User Satisfaction ◽

Information Overload ◽

Online Reviews ◽

Handheld Devices ◽

Word Count ◽

Significant Information ◽

Linguistic Inquiry ◽

Massive Information

<p class="0abstract">Mobile learning applications (apps) are increasingly and widely adopted for learning purposes and educational content delivery globally, especially with the massive means of accessing the internet done majorly on mobile handheld devices. Users often submit their feedback on use, experience and general satisfaction via the reviews and ratings given in the digital distribution platforms. With this massive information given through the reviews, it presents an opportunity to derives valuable insights which can be utilized for various reasons and by different stakeholders of these mobile learning apps. This large volume of online reviews creates significant information overload which presents a time-consuming task to read through all reviews. By combining text mining techniques of topic modeling using Latent Dirichlet Algorithm (LDA) and sentiment analysis using Linguistic Inquiry Word Count (LIWC), we analyze these user reviews. These techniques identify inherent topics in the reviews and identifies variables of user satisfaction of mobile learning apps. The thematic analysis done reveals different keywords which guide classification into the topics identified. Conclusively, the topics derived are important to app stakeholders for further modifications and evolution tasks.</p>

Linguistic Markers in Women’s Discussions on Miscarriage and Abortion Illustrate Psychological Responses to Their Experiences

Journal of Language and Social Psychology ◽

10.1177/0261927x20965643 ◽

2020 ◽

pp. 0261927X2096564

Author(s):

Kate G. Blackburn ◽

Weixi Wang ◽

Rhea Pedler ◽

Rachel Thompson ◽

Diana Gonzales

Keyword(s):

Emotion Regulation ◽

Text Analysis ◽

The Other ◽

Psychological Responses ◽

Word Count ◽

Future Directions ◽

Trauma Research ◽

Linguistic Markers ◽

This study analyzed thousands of women’s online conversations in relation to their miscarriage or abortion experiences, classified as unplanned and planned traumas, respectively. Linguistic Inquiry Word Count text analysis revealed that people experiencing a planned trauma use distancing language patterns in higher frequency and engage in emotion regulation more than those who experienced trauma unexpectedly. On the other hand, planned trauma conversations used more self-focused language and more social-based language. Implications and future directions for trauma research are discussed.

Analysing literacy and other psychological tendencies using linguistic profile in English expressive writing: Are students able but unwilling to write?

Indonesian Journal of Applied Linguistics ◽

10.17509/ijal.v9i1.12698 ◽

2019 ◽

Vol 9 (1) ◽

Author(s):

Bonita Lee ◽

Annisa Fitria ◽

Henndy Ginting

Keyword(s):

Critical Literacy ◽

Expressive Writing ◽

Business Students ◽

Word Count ◽

Significant Discrepancy ◽

Men And Women ◽

Global Competitiveness ◽

Linguistic Inquiry ◽

Global Population

The use of English in educational settings has become quite common in order to achieve global competitiveness. Given this fact, students are required to be fluent both in oral and written English. Unfortunately, the significant discrepancy is often found between the two. Students seemed to struggle when asked to elaborate their ideas in writing. With that in mind, this study would elaborate on the linguistic properties of students’ writings in order to understand the linguistic processes affecting such a discrepancy. Writings from a total of 205-business students were analysed using Linguistic Inquiry Word Count (LIWC2015) focusing on the linguistic and grammatical properties such as word counts, tenses associated words, adjectives, adverbs and so on. We found that our samples’ writing profile was significantly different from those of LIWC2015, especially in properties such word counts, six-letter words, verb and adjectives, as well as the use of I-related pronoun. For example, we found that our sample used a lot more difficult words while wrote less than half of the global population, suggesting their ability as well as unwillingness to write at the same time. With this main finding, we concluded that students come short in terms of critical literacy. In addition to that, we would also discuss the potential psychological implications (narcissistic tendency) as well as the differences between men and women styles in writing.

Proceedings of the 2015 International Conference on Social Science and Technology Education ◽

A Case Study of Text and Discourse Based on Juku, Coh-Metrix, and Linguistic Inquiry Word Count (LIWC)

10.2991/icsste-15.2015.261 ◽

2015 ◽

Author(s):

Liu Jia ◽

Shen Ying

Keyword(s):

Word Count ◽

Using LIWC to Analyze Participants’ Psychological Processing in Accounting JDM Research

Auditing A Journal of Practice & Theory ◽

10.2308/ajpt-2020-060 ◽

2021 ◽

Author(s):

Sanaz Aghazadeh ◽

Kris Hoang ◽

Bradley Pomeroy

Keyword(s):

Text Analysis ◽

Affective States ◽

Word Count ◽

Psycholinguistic Research ◽

Psychological Constructs ◽

Written Responses ◽

Control Procedures ◽

Linguistic Inquiry ◽

Psychological Processing

This paper provides methodological guidance for judgment and decision-making (JDM) researchers in accounting who are interested in using the Linguistic Inquiry Word Count (LIWC) text analysis program to analyze research participants’ written responses to open-ended questions. We discuss how LIWC’s measures of psychological constructs were developed and validated in psycholinguistic research. We then use data from an audit JDM study to illustrate the use of LIWC to guide researchers in identifying suitable measures, performing quality control procedures, and reporting the analysis. We also discuss research design considerations that will strengthen the inferences drawn from LIWC analysis. The paper concludes with examples where LIWC analysis has the potential to reveal participants’ deep, complex, effortful psychological processing and affective states from their written responses.

An Analysis of Linguistic Styles by Inferred Age in TV Dramas

Psychological Reports ◽

10.2466/pr0.99.2.351-356 ◽

2006 ◽

Vol 99 (2) ◽

pp. 351-356 ◽

Cited By ~ 2

Author(s):

Chang H. Lee ◽

Jongmin Park ◽

Young Seok Seo

Keyword(s):

Cognitive Development ◽

Spoken Language ◽

Analysis Program ◽

Word Count ◽

Negative Stereotypes ◽

Psychological Variables ◽

Language Analysis ◽

Linguistic Inquiry ◽

Aging People ◽

The Relationship

A language analysis program, Linguistic Inquiry and Word Count (LIWC), was successful in identifying various psychological variables. This study investigated the relationship between spoken language and age inferred from drama scripts of 162 characters, analyzed by the Korean-LIWC across 4 age categories (10–19, 20–39, 40–59, and 60–79 years). Analysis indicated that younger characters use fewer phrases, morphemes, nouns, auxiliary words, and adverbs than older characters, suggesting less cognitive development of younger characters. In addition, younger characters used less positive words for emotion and achievement than older characters. These data appear contrary to the negative stereotypes of aging people.

A computer’s understanding of literature

Scientific Study of Literature ◽

10.1075/ssol.1.1.03gra ◽

2011 ◽

Vol 1 (1) ◽

pp. 24-33 ◽

Cited By ~ 4

Author(s):

Arthur C. Graesser ◽

Nia Dowell ◽

Christian Moldovan

Keyword(s):

Computational Linguistics ◽

Discourse Processing ◽

Literary Texts ◽

Word Count ◽

Social Scientists ◽

Computer Tools ◽

Word Concreteness ◽

Political Speeches ◽

Everyone agrees that a computer could never understand and appreciate literature, but the fields of computational linguistics and discourse processing have made important advances in automatic detection of language and discourse characteristics. We have analyzed literary texts and political speeches with two computer tools, namely Coh-Metrix and Linguistic Inquiry Word Count (LIWC). Coh-Metrix provides hundreds of measures that funnel into 5 principal components: word concreteness, syntactic simplicity, referential cohesion, deep cohesion, and narrativity. LIWC classifies words on 80 categories, such as first person pronouns, negative emotions, and social words. This paper illustrates how computer tools can unveil new insights about literature and can empirically test claims by literary scholars and social scientists. Our approach offers a computational science of literature.

Language-Style Similarity and Social Networks

Psychological Science ◽

10.1177/0956797619894557 ◽

2019 ◽

Vol 31 (2) ◽

pp. 202-213 ◽

Cited By ~ 4

Author(s):

Balazs Kovacs ◽

Adam M. Kleinbaum

Keyword(s):

Social Networks ◽

Large Scale ◽

Online Reviews ◽

Word Count ◽

Data Set ◽

Friendship Formation ◽

Linguistic Style ◽

Large Scale Data ◽

Linguistic Inquiry ◽

Scale Data

This research demonstrates that linguistic similarity predicts network-tie formation and that friends exhibit linguistic convergence over time. In Study 1, we analyzed the linguistic styles and the emerging social network of a complete cohort of 285 students. In Study 2, we analyzed a large-scale data set of online reviews. In both studies, we collected data in two waves to examine changes in both social networks and linguistic styles. Using the Linguistic Inquiry and Word Count (LIWC) framework, we analyzed the text of students’ essays and of 1.7 million reviews by 159,651 Yelp reviewers. Consistent with our theory, results showed that similarity in linguistic style corresponded to a higher likelihood of friendship formation and persistence and that friendship ties, in turn, corresponded to a convergence in linguistic style. We discuss the implications of the coevolution of linguistic styles and social networks, which contribute to the formation of relational echo chambers.

Open Innovation in Digital Healthcare: Users’ Discrimination between Certified and Non-Certified mHealth Applications

Journal of Open Innovation Technology Market and Complexity ◽

10.3390/joitmc6040130 ◽

2020 ◽

Vol 6 (4) ◽

pp. 130

Author(s):

Ana Gessa ◽

Amor Jiménez ◽

Pilar Sancha

Keyword(s):

User Satisfaction ◽

Online Reviews ◽

Sampling Procedure ◽

User Reviews ◽

Quality Certification ◽

Two Samples ◽

Online User Reviews ◽

Categorical Structure ◽

Mhealth Apps

Mobile applications users consider it especially important to have quality certification, and particularly in an e-health context. However, if the app is certified, will user satisfaction be greater? This paper is intended to help answer that question. Therefore, with user satisfaction as a determinant of the quality of services, the purpose of the paper is to understand the extent to which certified and non-certified mHealth apps influence user experience. This was measured by online reviews and downloads. An empirical study was carried out with 50 mHealth apps (21 certified, 29 non-certified), which is a convenient sampling procedure. The Mahalanobis matching technique was used to test for significant differences between the groups. A comparative content analysis was performed on 6188 user comments and on app downloads. Non-parametric tests were preferred because the variables analyzed had a categorical structure. A log-linear model and advanced contingency tables were used to examine the more than two-way relationships of variables. The results show differences between the two samples (certified and non-certified mHealth apps). However, quality certification labels as a guarantee of the quality of apps do not have a modulating effect on the online reviews and downloads relationship. The model showed a statistically significant partial association between “certification” and “online user reviews” (Z = 2.174; sig = 0.042)] and between “download” and “online user reviews” (Z = 2.387; sig = 0.017).

The cultural influences of narrative content on consumers’ perceptions of helpfulness

International Journal of Market Research ◽

10.1177/14707853211023033 ◽

2021 ◽

pp. 147078532110230

Author(s):

Ning Fu

Keyword(s):

Rapid Development ◽

Cultural Influences ◽

Online Reviews ◽

The United States ◽

User Generated Content ◽

Text Analytics ◽

Word Count ◽

Cultural Backgrounds ◽

Linguistic Inquiry ◽

The Impact

The rapid development of text analytics enables marketers to obtain the information extracted from the narrative content in user-generated content (UGC). Recent studies have also demonstrated that people with different cultural backgrounds may express their opinions about their purchase in diverse manners. This study focuses on the impact of the narrative content of consumers’ perception of helpfulness. It first identifies four contextual dimensions to propose a theoretical model, demonstrating that perceptions of helpfulness may differ in respect to the consumers’ varied cultural backgrounds (e.g., individualism vs. collectivism). By using Linguistic Inquiry and Word Count (LIWC), the study empirically tests the hypotheses by analyzing 111,857 movie reviews collected for 167 American movies released both in the United States and in China from 2013 to 2016. The results reveal that individualist consumers perceive an online review that contains more self-description and future-focus content as helpful, whereas collectivist consumers rely more on online reviews containing social description and past-focus content.