Predicting Depression From Language-Based Emotion Dynamics: Longitudinal Analysis of Facebook and Twitter Status Updates (Preprint)

BACKGROUND Frequent expression of negative emotion words on social media has been linked to depression. However, metrics have relied on average values, not dynamic measures of emotional volatility. OBJECTIVE The aim of this study was to report on the associations between depression severity and the variability (time-unstructured) and instability (time-structured) in emotion word expression on Facebook and Twitter across status updates. METHODS Status updates and depression severity ratings of 29 Facebook users and 49 Twitter users were collected through the app MoodPrism. The average proportion of positive and negative emotion words used, within-person variability, and instability were computed. RESULTS Negative emotion word instability was a significant predictor of greater depression severity on Facebook (rs(29)=.44, P=.02, 95% CI 0.09-0.69), even after controlling for the average proportion of negative emotion words used (partial rs(26)=.51, P=.006) and within-person variability (partial rs(26)=.49, P=.009). A different pattern emerged on Twitter where greater negative emotion word variability indicated lower depression severity (rs(49)=−.34, P=.01, 95% CI −0.58 to 0.09). Differences between Facebook and Twitter users in their emotion word patterns and psychological characteristics were also explored. CONCLUSIONS The findings suggest that negative emotion word instability may be a simple yet sensitive measure of time-structured variability, useful when screening for depression through social media, though its usefulness may depend on the social media platform.

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Linguistic drivers of misinformation diffusion on social media during the COVID-19 pandemic

Italian Journal of Marketing ◽

10.1007/s43039-021-00026-9 ◽

2021 ◽

Author(s):

Giandomenico Di Domenico ◽

Annamaria Tuan ◽

Marco Visentin

Keyword(s):

Machine Learning ◽

Social Media ◽

New Technologies ◽

Fake News ◽

Conspiracy Theories ◽

Social Media Platform ◽

The Social ◽

Media Platform ◽

Textual Cues ◽

Twitter Users

AbstractIn the wake of the COVID-19 pandemic, unprecedent amounts of fake news and hoax spread on social media. In particular, conspiracy theories argued on the effect of specific new technologies like 5G and misinformation tarnished the reputation of brands like Huawei. Language plays a crucial role in understanding the motivational determinants of social media users in sharing misinformation, as people extract meaning from information based on their discursive resources and their skillset. In this paper, we analyze textual and non-textual cues from a panel of 4923 tweets containing the hashtags #5G and #Huawei during the first week of May 2020, when several countries were still adopting lockdown measures, to determine whether or not a tweet is retweeted and, if so, how much it is retweeted. Overall, through traditional logistic regression and machine learning, we found different effects of the textual and non-textual cues on the retweeting of a tweet and on its ability to accumulate retweets. In particular, the presence of misinformation plays an interesting role in spreading the tweet on the network. More importantly, the relative influence of the cues suggests that Twitter users actually read a tweet but not necessarily they understand or critically evaluate it before deciding to share it on the social media platform.

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Pace of Life in Cities and the Emergence of Town Tweeters

SAGE Open ◽

10.1177/2158244017745113 ◽

2017 ◽

Vol 7 (4) ◽

pp. 215824401774511 ◽

Cited By ~ 1

Author(s):

Alexander Jones Gross ◽

Dhiraj Murthy ◽

Lav R. Varshney

Keyword(s):

Social Media ◽

Population Density ◽

Economies Of Scale ◽

Gas Stations ◽

Pace Of Life ◽

The Social ◽

City Population ◽

Media Platform ◽

Twitter Users ◽

Ecological Correlation

Long-standing results in urban studies have shown correlation of population and population density to a city’s pace of life, empirically tested by examining whether individuals in bigger cities walk faster, spend less time buying stamps, or make greater numbers of telephone calls. Contemporary social media presents a new opportunity to test these hypotheses. This study examines whether users of the social media platform Twitter in larger and denser American cities tweet at a faster rate than their counterparts in smaller and sparser ones. Contrary to how telephony usage and productivity scale superlinearly with city population, the total volume of tweets in cities scales sublinearly. This is similar to the economies of scale in city infrastructures like gas stations. When looking at individuals, however, greater population density is associated with faster tweeting. The discrepancy between the ecological correlation and individual behavior is resolved by noting that larger cities have sublinear growth in the number of active Twitter users. This suggests that there is a more concentrated core of more active users that may serve an information broadcast function for larger cities, an emerging group of “town tweeters” as it were.

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Social network analysis of climate change discussion on Twitter during COP21

10.32920/ryerson.14645787 ◽

2021 ◽

Author(s):

Brittany E. Harris

Keyword(s):

Climate Change ◽

Social Media ◽

Social Network ◽

Network Analysis ◽

Social Media Platform ◽

The Public ◽

Climate Change Information ◽

The Social ◽

Media Platform ◽

Twitter Users

The public is increasingly relying on Twitter for climate change information; however, to date, this social media platform is poorly understood in terms of how climate change information is shared. This study evaluates discussions on Twitter during the 2015 United Nations Conference on Climate Change (COP21) to elucidate the social media platform’s role in communicating climate change information. For a five-day period, links embedded in a sample of tweets containing “#climatechange” were characterized, Twitter users were classified by the types of links they typically shared, and their degree centralities (the number of connections for each user) were measured. There was little skeptical content across all user categories; however, news links were more likely than non-news to contain content that is skeptical of climate change. Users who typically shared skeptical news links and users who typically shared non-skeptical non-news links exhibited a relatively high number of connections with other users.

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Self-Expression on Social Media

Personality and Social Psychology Bulletin ◽

10.1177/0146167216675332 ◽

2016 ◽

Vol 43 (1) ◽

pp. 60-70 ◽

Cited By ~ 20

Author(s):

Edward Orehek ◽

Lauren J. Human

Keyword(s):

Social Media ◽

Attachment Style ◽

Positive Emotion ◽

Self Esteem ◽

Social Perceptions ◽

Emotion Words ◽

The Social ◽

Social Media Platforms ◽

Media Platform ◽

Shed Light

Self-expression values are at an all-time high, and people are increasingly relying upon social media platforms to express themselves positively and accurately. We examined whether self-expression on the social media platform Twitter elicits positive and accurate social perceptions. Eleven perceivers rated 128 individuals (targets; total dyadic impressions = 1,408) on their impulsivity, self-esteem, and attachment style, based solely on the information provided in targets’ 10 most recent tweets. Targets were on average perceived normatively and with distinctive self-other agreement, indicating both positive and accurate social perceptions. There were also individual differences in how positively and accurately targets were perceived, which exploratory analyses indicated may be partially driven by differential word usage, such as the use of positive emotion words and self- versus other-focus. This study demonstrates that self-expression on social media can elicit both positive and accurate perceptions and begins to shed light on how to curate such perceptions.

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Differences in Emotional and Pain-Related Language in Tweets About Dentists and Medical Doctors: Text Analysis of Twitter Content (Preprint)

10.2196/preprints.10432 ◽

2018 ◽

Author(s):

Jan-Are K Johnsen ◽

Trude B Eggesvik ◽

Thea H Rørvik ◽

Miriam W Hanssen ◽

Rolf Wynn ◽

...

Keyword(s):

Social Media ◽

Dental Treatment ◽

Negative Emotion ◽

Medical Doctors ◽

Wide Audience ◽

Positive Attitudes ◽

Related Language ◽

The Social ◽

Media Platform ◽

Program Interface

BACKGROUND Social media provides people with easy ways to communicate their attitudes and feelings to a wide audience. Many people, unfortunately, have negative associations and feelings about dental treatment due to former painful experiences. Previous research indicates that there might be a pervasive and negative occupational stereotype related to dentists and that this stereotype is expressed in many different venues, including movies and literature. OBJECTIVE This study investigates the language used in relation to dentists and medical doctors on the social media platform Twitter. The purpose is to compare the professions in terms of the use of emotional and pain-related words, which might underlie and reflect the pervasive negative stereotype identified in relation to dentists. We hypothesized that (A) tweets about dentists will have more negative emotion-related words than those about medical doctors and (B) pain-related words occur more frequently in tweets about dentists than in those about medical doctors. METHODS Twitter content (“tweets”) about dentists and medical doctors was collected using the Twitter application program interface 140Dev over a 4-week period in 2015, scanning the search terms “dentist” and “doctor”. Word content of the selected tweets was analyzed using Linguistic Inquiry and Word Count software. The research hypotheses were investigated using nonparametric Wilcoxon-Mann-Whitney tests. RESULTS Over 2.3 million tweets were collected in total, of which about one-third contained the word “dentist” and about two-thirds contained the word “doctor.” Hypothesis A was supported since a higher proportion of negative words was used in tweets about dentists than in those about medical doctors (z=−10.47; P<.001). Similarly, tests showed a difference in the proportions of anger words (z=−12.54; P<.001), anxiety words (z=−6.96; P<.001), and sadness words (z=−9.58; P<.001), with higher proportions of these words in tweets about dentists than in those about doctors. Also, Hypothesis B was supported since a higher proportion of pain-related words was used in tweets about dentists than in those about doctors (z=−8.02; P<.001). CONCLUSIONS The results from this study suggest that stereotypes regarding dentists and dental treatment are spread through social media such as Twitter and that social media also might represent an avenue for improving messaging and disseminating more positive attitudes toward dentists and dental treatment.

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Social network analysis of climate change discussion on Twitter during COP21

10.32920/ryerson.14645787.v1 ◽

2021 ◽

Author(s):

Brittany E. Harris

Keyword(s):

Climate Change ◽

Social Media ◽

Social Network ◽

Network Analysis ◽

Social Media Platform ◽

The Public ◽

Climate Change Information ◽

The Social ◽

Media Platform ◽

Twitter Users

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What Drives Continuance Intention towards Social Media? Social Influence and Identity Perspectives

Sustainability ◽

10.3390/su12177081 ◽

2020 ◽

Vol 12 (17) ◽

pp. 7081 ◽

Cited By ~ 2

Author(s):

Athapol Ruangkanjanases ◽

Shu-Ling Hsu ◽

Yenchun Jim Wu ◽

Shih-Chih Chen ◽

Jo-Yu Chang

Keyword(s):

Social Media ◽

Social Identity ◽

New Media ◽

Social Influence ◽

Perceived Usefulness ◽

Continuance Intention ◽

Positive Effects ◽

The Social ◽

Media Platform ◽

Continuous Usage Intention

With the growth of social media communities, people now use this new media to engage in many interrelated activities. As a result, social media communities have grown into popular and interactive platforms among users, consumers and enterprises. In the social media era of high competition, increasing continuance intention towards a specific social media platform could transfer extra benefits to such virtual groups. Based on the expectation-confirmation model (ECM), this research proposed a conceptual framework incorporating social influence and social identity as key determinants of social media continuous usage intention. The research findings of this study highlight that: (1) the social influence view of the group norms and image significantly affects social identity; (2) social identity significantly affects perceived usefulness and confirmation; (3) confirmation has a significant impact on perceived usefulness and satisfaction; (4) perceived usefulness and satisfaction have positive effects on usage continuance intention. The results of this study can serve as a guide to better understand the reasons for and implications of social media usage and adoption.

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#GomorraLaSerie: Converging audience and enhanced authorship on twenty-first-century Italian screens

Modern Italy ◽

10.1017/s1353294400014800 ◽

2015 ◽

Vol 20 (4) ◽

pp. 335-349 ◽

Cited By ~ 2

Author(s):

Pierluigi Erbaggio

Keyword(s):

Social Media ◽

Quantitative Analysis ◽

Young People ◽

Qualitative Study ◽

Organised Crime ◽

First Century ◽

Social Media Platform ◽

Screen Viewing ◽

The Social ◽

Media Platform

Based on Roberto Saviano's book Gomorra (2006), production of the TV series Gomorra – La serie (2014) was met with scepticism as many feared it would glamorise organised crime and, consequently, attract young people toward Camorra affiliation. The series' bleak portrayal of criminals and criminality was offered as a response to such concerns. Despite the preoccupations, Gomorra – La serie was hugely successful and, because of its quality, was sold to other countries. In Italy, the series' success can be measured by the popularity of its Twitter hashtag #GomorraLaSerie. Engaged with Henry Jenkins' theories of media convergence and based on a corpus of tweets bearing this official hashtag, this article proposes a quantitative analysis and advances conclusions regarding the Italian TV audience and second-screen viewing practices. Additionally, through a qualitative study of Saviano's tweets about the series, it examines the writer's use of the social media platform as a tool of narrative continuity. Finally, the article highlights a few examples of fan-generated media and concludes with remarks regarding Saviano's problematic position at the centre of a transmedia object.

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Emotion Word Use by Adolescents Who Stutter: An Exploratory Study

Perspectives on Fluency and Fluency Disorders ◽

10.1044/ffd23.1.6 ◽

2013 ◽

Vol 23 (1) ◽

pp. 6-14

Author(s):

Corrin G. Richels ◽

Rogge Jessica

Keyword(s):

Positive Emotion ◽

Negative Emotion ◽

Conversational Speech ◽

Word Count ◽

Word Use ◽

Emotion Words ◽

Emotion Word ◽

Linguistic Inquiry ◽

Positive Valence ◽

Analyze Data

Purpose: Deficits in the ability to use emotion vocabulary may result in difficulties for adolescents who stutter (AWS) and may contribute to disfluencies and stuttering. In this project, we aimed to describe the emotion words used during conversational speech by AWS. Methods: Participants were 26 AWS between the ages of 12 years, 5 months and 15 years, 11 months-old (n=4 females, n=22 males). We drew personal narrative samples from the UCLASS database. We used Linguistic Inquiry and Word Count (LIWC) software to analyze data samples for numbers of emotion words. Results: Results indicated that the AWS produced significantly higher numbers of emotion words with a positive valence. AWS tended to use the same few positive emotion words to the near exclusion of words with negative emotion valence. Conclusion: A lack of diversity in emotion vocabulary may make it difficult for AWS to engage in meaningful discourse about negative aspects of being a person who stutters

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Study of Consumer Brand Following Intention on Instagram

International Journal of Online Marketing ◽

10.4018/ijom.2021040103 ◽

2021 ◽

Vol 11 (2) ◽

pp. 32-51

Author(s):

Simran Kaur Madan ◽

Payal S. Kapoor

Keyword(s):

Social Media ◽

Consumer Motivation ◽

Media Usage ◽

Consumer Skepticism ◽

Consumption Decisions ◽

The Social ◽

Media Platform ◽

Relationship Of ◽

The Relationship

The research, based on uses and gratifications theory, identifies consumer motivation and factors that influence consumers' intention to follow brands on the social media platform of Instagram. Accordingly, this study empirically examines the role of need for self-enhancement, the need for entertainment, and deal-seeking behaviour on the intention to follow brands on Instagram. Further, the study investigates the mediation of social media usage behaviour for consumption decisions on eliciting brand following behaviour. Moderation of consumer skepticism on the relationship of deal-seeking behaviour, and intention to follow brands is also investigated. Findings reveal a significant direct effect of need for self-enhancement, need for entertainment, and deal-seeking behaviour on intention to follow brands. Indirect effect of social media usage behaviour for consumption decisions was also significant; however, moderation of consumer skepticism was not found to be significant. The study will help marketers create engaging content that enables consumer-brand interactions.

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