Internet Slang in the Lexical Decision Task: Does Reaction Time for Word Recognition Correlate With Problematic Internet Use in Youth?
We proposed a complex diagnostics of problematic Internet use by implementing an online GPIUS3 survey and an experimental psycholinguistic technique (lexical decision task). Increasingly, researchers associate Internet use with problematic, destructive user behavior. Problematic Internet use (PIU) seems to be the most accurate definition of this type of behavior, which emphasizes the destructive potential of a person's online interaction with the global network. According to this approach, the Internet itself is not considered as a direct cause of changes in behavior and personality traits. The role of the negative consequences of the Internet use for a particular individual is emphasized. The stimuli for the lexical decision task (n = 96) were grouped in pairs: 1) thematically related slang and common words (for example, kheyter - nenavistnik, n = 24); 2) thematically unrelated slang and common words (for example, kheyter - rukav, n = 24); 3) common words and nonwords (for example, nenavistnik - stskystsk, rukav - skvuitkhe, n = 48). All the pairs were randomly presented to the participant. Each participant met slang and neutral (common) words twice in different conditions (in different pairs of stimuli). The sample comprised 106 Russian-speaking students aged 12 to 22 (M = 19.44, SD = 1.54), including females (n = 76) and males (n = 30). Using linear-mixed effects modeling, we found significant reaction time predictors which were relevant to Internet jargon processing. These predictors are cognitive preoccupation of adolescents with an effect size of -0.21 SD and mood regulation with 0.14 SD effect size. The number of hours a day spent on the Internet was not significant as a reaction time predictor in this model. The average frequency of word pairs (average Zipf-value) had a significant effect on reaction time reduction (-0.18 SD). The random effects of the participant and stimulus on reaction time were also significant in the study. The study revealed that individuals with a higher cognitive preoccupation on the Internet recognized Internet slang words significantly faster. This effect is most likely explained by the volume of individual slang vocabulary size. The stimulus-type effect showed the expected but weak trend: thematically unrelated slang and common words were recognized slower by an average of 0.08 SD of reaction time. The assumption is that the vocabulary of persons, who actively use social networking and the Internet in general, is organized according to the thematic principle, and the processing of slang-common words pairs recognition requires further verification in experimental studies.
Keywords
youth,
problematic Internet use,
Internet slang,
lexical decision taskAuthors
Vlasov Mikhail S. | Shukshin Altai State University for Humanities and Pedagogy | vlasov@bigpi.biysk.ru ; vlasov_mikhailo@mail.ru |
Sychev Oleg A. | Shukshin Altai State University for Humanities and Pedagogy | osn1@mail.ru |
Всего: 2
References
Герасимова А.А., Холмогорова А.Б. Общая шкала проблемного использования интернета: апробация и валидизация в российской выборке третьей версии опросника // Консультативная психология и психотерапия. 2018. Т. 26, № 3. C. 56-79. doi: 10.17759/cpp.2018260304
Кочетков Н.В. Интернет-зависимость и зависимость от компьютерных игр в трудах отечественных психологов // Социальная психология и общество. 2020. Т. 11, № 1. С. 27-54. https://doi.org/10.17759/sps.2020110103
Hui-Yin Hsu, Shiangkwei Wang. The Impact of Using Blogs on College Students' Reading Comprehension and Learning Motivation // Literacy Research and Instruction. 2010. Vol. 50, № 1. Р. 68-88. doi: 10.1080/19388070903509177
De Wever B., Van Keer H., Schellens T., Valcke M. Assessing collaboration in a wiki: The reliability of university students' peer assessment // Internet and Higher Education. 2011. Vol. 14, is. 4. Р. 201-206. https://doi.org/10.1016/j.iheduc.2011.07.003
Sung Y.-T., Chang K.-E., Liu T.-C. The effects of integrating mobile devices with teaching and learning on students' learning performance: A meta-analysis and research synthesis // Computers & Education. 2016. Vol. 94. Р. 252-275. https://doi.org/10.1016/j.compedu.2015.11.008
Burke Moira, Kraut Robert E. The Relationship Between Facebook Use and WellBeing Depends on Communication Type and Tie Strength // Journal of Computer-Mediated Communication. 1 July 2016. Vol. 21, is. 4. P. 265-281. https://doi.org/10.1111/jcc4.12162
Бовина И.Б., Дворянчиков Н.В. Поведение онлайн и офлайн: к вопросу о возможности прогноза // Культурно-историческая психология. 2020. Т. 16, № 4. С. 98-108. doi: 10.17759/chp.2020160410
Young K.S.Internet addiction: The emergence of a new clinical disorder // CyberPsychology & Behavior. 1998. Vol. 1, is. 3. P. 237-244. doi: 10.1089/cpb.1998.1.25
Demetrovics Z., Kiraly O.Internet/gaming addiction is more than heavy use over time: Commentary on Baggio and colleagues // Addiction. 2016. Vol. 111 (3). P. 523-524. doi: 10.1111/add.13244
Wong T.Y., Yuen K.S.L., Li W.O. A basic need theory approach to problematic Internet use and the mediating effect of psychological distress // Front. Psychol. 2015. Vol. 5. Р. 1562. doi: 10.3389/fpsyg.2014.01562
Seabrook E.M., Kern M.L., Rickard N.S. Social Networking Sites, Depression, and Anxiety: A Systematic Review // JMIR mental health. 2016. Vol. 3, № 4. Р. e50. https://doi.org/10.2196/mental.5842
Toth-Kiraly I., Morin A.J.S., Hietajarvi L., Salmela-Aro K. Longitudinal Trajectories, Social and Individual Antecedents, and Outcomes of Problematic Internet Use Among Late Adolescents // Child Development. Jul/Aug 2021. Vol. 92, is. 4. pe653-e673. doi: 10.1111/cdev.13525
Wang P., Wang J., Yan Y., Si Y., Zhan X., Tian Y. Relationship Between Loneliness and Depression Among Chinese Junior High School Students: The Serial Mediating Roles of Internet Gaming Disorder, Social Network Use, and Generalized Pathological Internet Use // Front. Psychol. 2021. Vol. 11. Р. 529665. doi: 10.3389/fpsyg.2020.529665
Davis R.A. A cognitive-behavioral model of pathological Internet use // Computers in Human Behavior. 2001. Vol. 17 (2). P. 187-195. doi: 10.1016/S0747-5632(00)00041-8
Caplan S.E. Theory and measurement of generalized problematic Internet use: A two-step approach: Advancing Educational Research on Computer-supported Collaborative Learning (CSCL) through the use of gStudy CSCL Tools // Computers in Human Behavior. 2010. Vol. 26 (5). P. 1089-1097. doi: 10.1016/j.chb.2010.03.012
Caplan S.E. Problematic Internet use and psychosocial well-being: development of a theory-based cognitive-behavioral measurement instrument // Computers in Human Behavior. 2002. Vol. 18. P. 553-575. doi: 10.1016/S0747-5632(02)00004-3
Meyer D.E., Schvaneveldt R.W. Facilitation in recognizing pairs of words: Evidence of a dependence between retrieval operations // Journal of Experimental Psychology. 1971. Vol. 90. Р. 227-234.
Mainz N., Shao Z., Brysbaert M., Meyer A.S. Vocabulary Knowledge Predicts Lexical Processing: Evidence from a Group of Participants with Diverse Educational Backgrounds // Front. Psychol. 2017. Vol. 8. Р. 1164. doi: 10.3389/fpsyg.2017.01164
Butler B., Hains S. Individual differences in word recognition latency // Memory & Cognition. 1979. Vol. 7. Р. 68-76.
Chateau D., Jared D. Exposure to print and word recognition processes // Memory & Cognition. 2000. Vol. 28, is. 1. Р. 143-153. https://doi.org/10.3758/bfD3211582
Clark D.M., Teasdale J.D., Broadbent D.E., Martin M. Effect of mood on lexical decisions // Bulletin of the Psychonomic Society. 1983. Vol. 21. Р. 175-178. https://doi.org/10.3758/BF03334679
Richards A., French C.C. An anxiety-related bias in semantic activation when processing threat/neutral homographs // The Quarterly Journal of Experimental Psychology Section A. 1992. Vol. 45, № 3. Р. 503-525. doi: 10.1080/02724989208250625
Lewellen M.J., Goldinger S.D., Pisoni D.B., Greene B.G. Lexical familiarity and processing efficiency: individual differences in naming, lexical decision, and semantic categorization // Journal of experimental psychology. General. 1993. Vol. 122 (3). Р. 316-330. https://doi.org/10.1037//0096-3445.122.3.316
Olafson K.M., Ferraro F.R. Effects of emotional state on lexical decision performance // Brain and cognition. 2001. Vol. 45. Р. 15-20. https://doi.org/10.1006/brcg.2000.1248
Briesemeister B.B., Kuchinke L., Jacobs A.M. Discrete Emotion Effects on Lexical Decision Response Times // PLoS ONE. 2011. Vol. 6, № 8. e23743. https://doi.org/10.1371/journal.pone.0023743
Vinson D., Ponari M., Vigliocco G. How does emotional content affect lexical processing? // Cognition and Emotion. 2014. Vol. 28, № 4. Р. 737-746. doi: 10.1080/02699931.2013.851068
Stip E., Lecours A.R., Chertkow H., Elie R., O'Connor K. Influence of affective words on lexical decision task in major depression // Journal of psychiatry & neuroscience : JPN. 1994. Vol. 19 (3). Р. 202-207.
Besche-Richard C., Passerieux C., Hardy-Bayle M. Lexical decision tasks in depressive patients: Semantic priming before and after clinical improvement // European Psychiatry. 2002. Vol. 17, is. 2. Р. 69-74. doi: 10.1016/S0924-9338(02)00630-2
Власов М.С., Сычев О.А. Личностные факторы времени реакции в задаче лексического решения со стимулами различной эмоциональной окраски // Личность, интеллект, метакогниции: исследовательские подходы и образовательные практики: материалы II Международной научно-практической конференции. Калуга, 2017. С. 614-622.
Власов М.С., Сычев О.А. Взаимодействие эмоциональных и лингвистических факторов в процессе переработки лексической информации (на материале имен существительных русского языка) // Вестник Томского государственного университета. Филология. 2018. № 52. С. 18-52. doi: 10.17223/19986645/52/2
Stoet G. PsyToolkit - A software package for programming psychological experiments using Linux // Behavior Research Methods. 2010. Vol. 42, is. 4. Р. 1096-1104.
Stoet G. PsyToolkit: A novel web-based method for running online questionnaires and reaction-time experiments // Teaching of Psychology. 2017. Vol. 44, is. 1. Р. 24-31.
Kim J., Gabriel U., Gygax P. Testing the effectiveness of the Internet-based instrument PsyToolkit: A comparison between web-based (PsyToolkit) and lab-based (E-Prime 3.0) measurements of response choice and response time in a complex psycholinguistic task // PloS one. 2019. Vol. 14, № 9. e0221802. https://doi.org/10.1371/journal.pone.0221802
Snider N., Arnon I. A unified lexicon and grammar? Compositional and non-compositional phrases in the lexicon // Frequency effects in language representation / eds. by D. Divjak, S. Gries. Berlin : Mouton de Gruyter, 2012. Р. 127-164.
Baayen R.H., Milin P. Analyzing reaction times // International Journal of Psychological Research. 2015. Vol. 3, № 2. P. 12-28. doi: 10.21500/20112084.807
Young K.S., Rogers R.C. The relationship between depression and internet addiction // Cyberpsychol. Behav. 1998. Vol. 1. Р. 178-183. doi: 10.1089/cpb.1998.1.25
Engelberg E., Sjoberg L.Internet use, social skills, and adjustment // CyberPsychol. Behav. 2004. Vol. 7. Р. ' 41-47. doi: 10.1089/109493104322820101
Sukenick S. Alone together: why we expect more from technology and less from each other by turkle, sherry //j. Anal. Psychol. 2012. Vol. 57. Р. 128-129. doi: 10.1080/02650533.2013.769209
Jia W.L. Causes, behavioral manifestations and social hazards of internet addiction //j. Shenyang Agricult. University (Social Sciences Edition). 2005. Vol. 7. Р. 504-505. doi: 10.3969/j.issn.1008-9713.2005.04.040
Zou X.M., Ding B.G., Yu J., Zhang X.P., Zou H. The influence of network on adolescent health and counter-measures //j. Clin. Psychosomatic Dis. 2007. Vol. 13. Р. 178-179. doi: 10.3969/j.issn.1672-187X.2007.02.046
Eroglu M., Pamuk M., Pamuk K. Investigation of problematic internet usage of university students with psychosocial levels at different levels // Procedia - Social Behav. Sci. 2013. Vol. 103. Р. 551-557. doi: 10.1016/j.sbspro.2013.10.372
Sanders C.E., Field T.M., Diego M., Kaplan M. The relationship of internet use to depression and social isolation among adolescents // Adolescence. 2000. Vol. 35. Р. 237-242. doi: 10.1016/S0001-6918(00)00038-X
Odaci H., C.ikrikci O. Problematic internet use in terms of gender, attachment styles and subjective well-being in university students // Comp. Hum. Behav. 2014. Vol. 32. Р. 6166. doi: 10.1016/j.chb.2013.11.019
Lu X., Yeo K.J. Pathological internet use among Malaysia University students: risk factors and the role of cognitive distortion // Comp. Hum. Behav. 2015. Vol. 45. Р. 235-242. doi: 10.1016/j.chb.2014.12.021
Liu Q.X., Fang X.Y., Deng L.Y., Zhang J.T. Parent-adolescent communication, parental internet use and internet-specifific norms and pathological internet use among chinese adolescents // Comp. Hum. Behav. 2012. Vol. 28. Р. 1269-1275. doi: 10.1016/j.chb.2012.02.010