Parental Mentalizing During a Pandemic: Use of Mental-State Language on Parenting Social Media Before and During the COVID-19 Pandemic

The COVID-19 pandemic has been a demanding caregiving context for parents, particularly during lockdowns. In this study, we examined parental mentalization, parents’ proclivity to consider their own and their child’s mental states, during the pandemic, as manifested in mental-state language (MSL) on parenting social media. Parenting-related posts on Reddit from two time periods in the pandemic in 2020, March to April (lockdown) and July to August (postlockdown), were compared with time-matched control periods in 2019. MSL and self–other references were measured using text-analysis methods. Parental mentalization content decreased during the pandemic: Posts referred less to mental activities and to other people during the COVID-19 pandemic and showed decreased affective MSL, cognitive MSL, and self-references specifically during lockdown. Father-specific subreddits exhibited strongest declines in mentalization content, whereas mother-specific subreddits exhibited smaller changes. Implications on understanding associations between caregiving contexts and parental mentalization, gender differences, and the value of using social-media data to study parenting and mentalizing are discussed.

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Maternal mental state language is associated with trajectories of Chinese immigrant children’s emotion situation knowledge

International Journal of Behavioral Development ◽

10.1177/0165025418783271 ◽

2018 ◽

Vol 43 (1) ◽

pp. 43-52 ◽

Cited By ~ 4

Author(s):

Stacey N. Doan ◽

Helen Y. Lee ◽

Qi Wang

Keyword(s):

Mental State ◽

Cultural Context ◽

Mental States ◽

European American ◽

Chinese Immigrant ◽

Children's Emotion ◽

Mental State Language ◽

And Behaviors ◽

Over Time ◽

State Language

We investigated the role of mothers’ references to mental states and behaviors and children’s emotion situation knowledge (ESK) in a prospective, cross-cultural context. European American mothers ( n = 71) and Chinese immigrant mothers ( n = 60) and their children participated in the study. Maternal references to mental states and behaviors were assessed at Time 1 when children were three years of age. ESK was assessed when children were 3, 3.5, and 4.5 years of age. Multi-group latent growth curve analyses were used to model children’s growth in ESK over time, as well as relations between mental state language and references to behaviors on children’s trajectories. Results indicated that maternal references to mental states were associated with concurrent levels of ESK for European American children, and change over time for the Chinese immigrant children. Maternal references to behaviors were negatively associated with concurrent ESK for both groups.

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Mental terms in mothers' and children's speech: similarities and relationships

Journal of Child Language ◽

10.1017/s0305000900011594 ◽

1992 ◽

Vol 19 (3) ◽

pp. 617-631 ◽

Cited By ~ 62

Author(s):

David Furrow ◽

Chris Moore ◽

Jane Davidge ◽

Lorraine Chiasson

Keyword(s):

Theory Of Mind ◽

Mental State ◽

Mental States ◽

Mental Processes ◽

Mental State Language ◽

Mother And Child ◽

Children's Attention ◽

Children's Speech ◽

State Language

ABSTRACTIn this study, mental terms in mothers' and their children's speech at two and three years of age were studied in order to examine the relationships between maternal and child use. Nineteen mother and child dyads were videotaped for one hour on each of two days when the children were 2;0 and again for two one-hour sessions on separate days when they were 3;0, and mental terms were noted. The utterances in which mental terms were used were coded for function. Results supported the existing picture of children's mental term use. Few terms appeared at 2;0, but many were used at 3;0 with think and know predominating. Mental terms occurred more commonly in utterances used to regulate the interaction between the participants than in utterances referring to mental states. Children's mental term use mirrored that of their mothers. Further, mothers' use of mental terms for particular functions when their children were 2;0 predicted their children's use at 3;0. While allowing no conclusions about causation, our findings suggest that the development of mental state language, and thus presumably a theory of mind, is fostered by the linguistic environment. Specifically, it is argued that the tendency of mothers to focus their children's attention on mental processes by talking about them and, more importantly, by using utterance types which conceivably direct the children to reflect on their own mental states, is associated with children's use of mental terms.

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Geolocation prediction in social media data using text analysis: A review

2018 International Conference on Information and Communications Technology (ICOIACT) ◽

10.1109/icoiact.2018.8350674 ◽

2018 ◽

Author(s):

Muhammad Nur Yasir Utomo ◽

Teguh Bharata Adji ◽

Igi Ardiyanto

Keyword(s):

Social Media ◽

Text Analysis ◽

Social Media Data ◽

Media Data

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Language left behind on social media exposes the emotional and cognitive costs of a romantic breakup

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2017154118 ◽

2021 ◽

Vol 118 (7) ◽

pp. e2017154118

Author(s):

Sarah Seraj ◽

Kate G. Blackburn ◽

James W. Pennebaker

Keyword(s):

Social Media ◽

Cognitive Processing ◽

Meaning Making ◽

Short Term ◽

Analytic Thinking ◽

Social Media Data ◽

Left Behind ◽

Time Periods ◽

Romantic Breakup ◽

Media Data

Using archived social media data, the language signatures of people going through breakups were mapped. Text analyses were conducted on 1,027,541 posts from 6,803 Reddit users who had posted about their breakups. The posts include users’ Reddit history in the 2 y surrounding their breakups across the various domains of their life, not just posts pertaining to their relationship. Language markers of an impending breakup were evident 3 mo before the event, peaking on the week of the breakup and returning to baseline 6 mo later. Signs included an increase in I-words, we-words, and cognitive processing words (characteristic of depression, collective focus, and the meaning-making process, respectively) and drops in analytic thinking (indicating more personal and informal language). The patterns held even when people were posting to groups unrelated to breakups and other relationship topics. People who posted about their breakup for longer time periods were less well-adjusted a year after their breakup compared to short-term posters. The language patterns seen for breakups replicated for users going through divorce (n = 5,144; 1,109,867 posts) or other types of upheavals (n = 51,357; 11,081,882 posts). The cognitive underpinnings of emotional upheavals are discussed using language as a lens.

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Crosslinguistic Developmental Consistency in the Composition of Toddlers’ Internal State Vocabulary: Evidence from Four Languages

Child Development Research ◽

10.1155/2014/575142 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 4

Author(s):

Susanne Kristen ◽

Sabrina Chiarella ◽

Beate Sodian ◽

Tiziana Aureli ◽

Maria Genco ◽

...

Keyword(s):

Mental State ◽

Internal State ◽

Mental States ◽

Typically Developing ◽

Questionnaire Data ◽

Typically Developing Children ◽

Psychological Understanding ◽

Parental Questionnaire ◽

Mental State Language ◽

State Language

Mental state language, emerging in the second and third years of life in typically developing children, is one of the first signs of an explicit psychological understanding. While mental state vocabulary may serve a variety of conversational functions in discourse and thus might not always indicate psychological comprehension, there is evidence for genuine references to mental states (desires, knowledge, beliefs, and emotions) early in development across languages. This present study presents parental questionnaire data on the composition of 297 toddler-aged (30-to 32-month-olds) children’s internal state vocabulary in four languages: Italian, German, English, and French. The results demonstrated that across languages expressions for physiological states (e.g., hungry and tired) were among the most varied, while children’s vocabulary for cognitive entities (e.g., know and think) proved to be least varied. Further, consistent with studies on children’s comprehension of these concepts, across languages children’s mastery of volition terms (e.g., like to do and want) preceded their mastery of cognition terms. These findings confirm the cross-linguistic consistency of children’s emerging expression of abstract psychological concepts.

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Perbandingan Fitur Ekstraksi Untuk Klasifikasi Emosi Pada Sosial Media

Jurnal Ilmiah SINUS ◽

10.30646/sinus.v18i2.457 ◽

2020 ◽

Vol 18 (2) ◽

pp. 21

Author(s):

Riska Dwi Handayani ◽

Kusrini Kusrini ◽

Hanif Al Fatta

Keyword(s):

Social Media ◽

Social Interaction ◽

Information Sharing ◽

Human Nature ◽

Mental States ◽

Social Media Data ◽

Comparative Feature ◽

N Gram ◽

Bayes Algorithm ◽

Media Data

Emotions are complex conscious experiences characterizing mental states, such as excitement, anger, love, fear, and so on, as part of important human nature. Nowadays, many people express themselves as a reflection of their personality using social media. Social Media grows and becomes a method for social interaction and information sharing. Based on that, researchers tried to use social media data to classify someone's emotions. Emotional detection of text from social media is a field of research that is gaining a high interest, especially for the sake of emotional analysis. To be able to classify such emotions, researchers use comparative feature comparison and algorithms classification. The comparison of features in this research is the extraction features TF-IDF and N-gram which are then classified using Naïve bayes algorithm. However, before the extraction feature is applied, there is a pre-processing text technique using several methods: Case Folding, Stopword Removal, and Stemming. Based on this research, techniques of extraction features in this research generating the highest accuracy value after the classification method is the TF-IDF with an accuracy value of 80%, 98% for the highest value of precision in measurement of “pleasure” emotion, 99% for the highest recall value is in “happy” emotion, and 95% for the highest F1-score value in “pleasure” emotion.

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