Abstract
Young people use slang for identifying themselves with a particular social group, gaining social recognition and respect from that group, and expressing their emotional state. One feature of Internet slang is its active use by youth in online communication, which, under certain conditions, may cause problematic Internet use (PIU). We conducted two studies in young Russian speakers (n1 = 115, n2 = 106). In study 1, participants were asked to rate a set of slang and common words using Self-Assessment Manikin. The study revealed that the most reliable predictor of higher emotional ratings was word familiarity. There were no significant effects of slang vs. common words or word frequency. In study 2, we used a dual lexical decision task to reveal the effects of word characteristics and propensity for PIU on reaction time (RT) for Internet slang words in pairs with semantically related vs. unrelated common words. Study 2 did not reveal any significant semantic priming effect. Word frequency was a significant predictor of lexical decision facilitation. Common, but not slang, word valence and dominance significantly affected RT in the opposite direction. Individuals with higher cognitive preoccupation with the Internet responded significantly faster, while those more likely to use online communication for mood regulation responded significantly slower to the stimuli. Apparently, on explicit and implicit levels, in-depth knowledge of Internet slang can be one the PIU markers. The results are discussed in line with Davis’ approach to determining the general pathological Internet use.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability Statement
The data and materials from Study 1 and Study 2 are publicly available at the Open Science Framework website: https://osf.io/fwgqn/?view_only=fdc243b7b9164e1cbe5a6b5a8afae4d0.
Notes
The data were retrieved from: https://exlibris.ru/news/digital-2021-glavnaya-statistika-po-rossii-i-vsemu-miru/.
The Zipf coefficient makes it possible to compare word frequencies extracted from different corpora and databases, regardless of the corpora size. Zipf coefficient = log10(fpmw) + 3 or log10(fpmw*1000), where fpmw is the frequency of a particular word per million words. Fpmw was retrieved from the General Internet Corpus of the Russian Language: http://www.webcorpora.ru/ (Belikov et al., 2013a, 2013b).
According to the General Internet Corpus of the Russian Language, word frequency for the stimulus words did not exceed 10 ipm.
References
Abdrakhmanova, G. I., Vasilkovsky, S. A., Vishnevsky, K. O., Gohberg, L. M., Demidkina, O. V., Demjyanova, A. V., Kovaleva, G. G., Kotsemir, M. N., Kuznetsova, I. A., Ozerova, O. K., Polyakova, V. V., Ratay, N. V., Ryzhikova, Z. A., Streltsova, E. A., Utyatina, K. E., Fridlyanova, S. Y., & Shugal, N. B. (2022). Digital economy: 2022: A brief statistical collection. National Research University “Higher School of Economics.” NRU HSE. https://doi.org/10.17323/978-5-7598-2599-9 (in Russian).
Adams, M. (2009). Slang: the people’s poetry. Oxford University Press. ISBN 9780195314632
Arpaci, I., Kesici, Ş, & Baloğlu, M. (2018). Individualism and internet addiction: The mediating role of psychological needs. Internet Research, 28(2), 293–314. https://doi.org/10.1108/intr-11-2016-0353
Baker, T. B., Piper, M. E., McCarthy, D. E., Majeskie, M. R., & Fiore, M. C. (2004). Addiction motivation reformulated: An affective processing model of negative reinforcement. Psychological Review, 111, 33–51. https://doi.org/10.1037/0033-295X.111.1.33
Baldwin, M. W., Fehr, B., Keedian, E., Seidel, M., & Thomson, D. W. (1993). An exploration of the relational schemata underlying attachment styles: Self-report and lexical decision approaches. Personality and Social Psychology Bulletin, 19(6), 746–754. https://doi.org/10.1177/0146167293196010
Barriga-Paulino, C. I., Guerreiro, M., Faísca, L., & Reis, A. (2022). Does emotional valence modulate word recognition? A behavioral study manipulating frequency and arousal. Acta Psychologica, 223, 103484. https://doi.org/10.1016/j.actpsy.2021.103484
Belikov V., Kopylov N., Piperski A., Selegey V., Sharoff S. (2013a). Corpus as language: From scalability to register variation. In Dialogue, Russian International Conference on Computational Linguistics, Bekasovo. https://www.dialog-21.ru/digests/dialog2013/materials/pdf/BelikovVI.pdf
Belikov V., Kopylov N., Piperski A., Selegey V., Sharoff S. (2013b). Big and diverse is beautiful: A large corpus of Russian to study linguistic variation. In Web as Corpus Workshop (WAC-8). http://www.webcorpora.ru/wp-content/uploads/2015/10/wac8-proceedings.pdf
Bermúdez-Margaretto, B., Shtyrov, Y., Beltrán, D., Cuetos, F., & Dominguez, A. (2020). Rapid acquisition of novel written word-forms: ERP evidence. Behavioral and Brain Functions: BBF, 16. https://doi.org/10.1186/s12993-020-00173-7
Bernat, E., Bunce, S., & Shevrin, H. (2001). Event-related brain potentials differentiate positive and negative mood adjectives during both supraliminal and subliminal visual processing. International Journal of Psychophysiology: Official Journal of the International Organization of Psychophysiology, 42(1), 11–34. https://doi.org/10.1016/s0167-8760(01)00133-7
Borkenau, P., Paelecke, M., & Yu, R. (2010). Personality and lexical decision times for evaluative words. European Journal of Personality, 24(2), 123–136. https://doi.org/10.1002/per.747
Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry, 25(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9
Bradley, M. M., & Lang, P. J. (1999). Affective norms for English words (ANEW): Instruction manual and affective ratings. University of Florida.
Bradley, M. M., & Lang, P. J. (2007). The international affective digitized sounds (2nd Edition; IADS-2): Affective ratings of sounds and instruction manual. University of Florida.
Brysbaert, M., Mandera, P., & Keuleers, E. (2018). The word frequency effect in word processing: An updated review. Current Directions in Psychological Science, 27(1), 45–50. https://doi.org/10.1177/0963721417727521
Bucholtz, M. (2000). Language and youth culture. American Speech 75(3), 280-283 https://www.muse.jhu.edu/article/2731
Campos-Melady, M., & Smith, J. E. (2012). Memory associations between negative emotions and alcohol on the lexical decision task predict alcohol use in women. Addictive Behaviors, 37(1), 60–66. https://doi.org/10.1016/j.addbeh.2011.08.010
Caplan, S. E. (2002). Problematic Internet use and psychosocial well-being: Development of a theory-based cognitive-behavioral measurement instrument. Computers in Human Behavior, 18, 553–575. https://doi.org/10.1016/S0747-5632(02)00004-3
Caplan, S. E. (2010). Theory and measurement of generalized problematic Internet use: A two-step approach. Computers in Human Behavior, 26(5), 1089–1097. https://doi.org/10.1016/j.chb.2010.03.012
Challis, B. H., & Krane, R. V. (1988). Mood induction and the priming of semantic memory in a lexical decision task: Asymmetric effects of elation and depression. Bulletin of the Psychonomic Society, 26(4), 309–312. https://doi.org/10.3758/BF03337666
Citron, F. M. M., Weekes, B. S., & Ferstl, E. C. (2014a). Arousal and emotional valence interact in written word recognition. Language, Cognition and Neuroscience, 29(10), 1257–1267. https://doi.org/10.1080/23273798.2014.897734
Citron, F., Weekes, B., & Ferstl, E. (2014b). How are affective word ratings related to lexicosemantic properties? Evidence from the Sussex Affective Word List. Applied Psycholinguistics, 35(2), 313–331. https://doi.org/10.1017/S0142716412000409
Clark, D. M., Teasdale, J. D., Broadbent, D. E., & Martin, M. (1983). Effect of mood on lexical decisions. Bulletin of the Psychonomic Society, 21(3), 175–178. https://doi.org/10.3758/BF03334679
Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use. Computers in Human Behavior, 17(2), 187–195. https://doi.org/10.1016/s0747-5632(00)00041-8
Deci, E. L., & Ryan, R. M. (2008). Self-determination theory: A macrotheory of human motivation, development, and health. Canadian Psychology, 49, 182–185. https://doi.org/10.1037/A0012801
Eble, C. (1996). Slang and sociability: In-group language among college students. University of North Carolina Press.
Estes, Z., & Adelman, J. S. (2008). Automatic vigilance for negative words in lexical decision and naming: Comment on Larsen, Mercer, and Balota (2006). Emotion, 8(4), 441–444. https://doi.org/10.1037/1528-3542.8.4.441
Fischler, I. (1977). Semantic facilitation without association in a lexical decision task. Memory & Cognition, 5, 335–339. https://doi.org/10.3758/BF03197580
Geer, J. H., & Bellard, H. S. (1996). Sexual content induced delays in unprimed lexical decisions: Gender and context effects. Archives of Sexual Behavior, 25(4), 379–395. https://doi.org/10.1007/BF02437581
Gerasimova, A. A., & Kholmogorova, A. B. (2018). The generalized problematic internet use scale 3 modified version: Approbation and validation on the Russian sample [Elektronnyi resurs]. Konsul’tativnaya Psikhologiya i Psikhoterapiya = Counseling Psychology and Psychotherapy, 26(3), 56–79. https://doi.org/10.17759/cpp.2018260304. (in Russian).
Green, J. (2016). Slang: A very short introduction. Oxford University Press. ISBN 978–0–19–872953–2
Greitemeyer, T., Mügge, D. O., & Bollermann, I. (2014). Having responsive Facebook friends affects the satisfaction of psychological needs more than having many Facebook friends. Basic and Applied Social Psychology, 36(3), 252–258. https://doi.org/10.1080/01973533.2014.900619
Hinojosa, J. A., Moreno, E. M., & Ferré, P. (2020). On the limits of affective neurolinguistics: A “universe” that quickly expands. Language, Cognition and Neuroscience, 35(7), 877–884. https://doi.org/10.1080/23273798.2020.1761988
Hofmann, M. J., Kuchinke, L., Tamm, S., Võ, M. L., & Jacobs, A. M. (2009). Affective processing within 1/10th of a second: High arousal is necessary for early facilitative processing of negative but not positive words. Cognitive, Affective & Behavioral Neuroscience, 9(4), 389–397. https://doi.org/10.3758/9.4.389
Kalita, I. V. (2013). Stylistic transformations of Russian substandards, or a book about slang. Dixy Press. ISBN 978-5-905490-15-6 (in Russian)
Kazanas, S. A., & Altarriba, J. (2015). The automatic activation of emotion and emotion-laden words: Evidence from a masked and unmasked priming paradigm. The American Journal of Psychology, 128(3), 323–336. https://doi.org/10.5406/AMERJPSYC.128.3.0323
Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (2005). International affective picture system (IAPS): Affective ratings of pictures and instruction manual. University of Florida.
Laurinavichyute, A. K., Sekerina, I. A., Alexeeva, S., Bagdasaryan, K., & Kliegl, R. (2019). Russian sentence corpus: Benchmark measures of eye movements in reading in Russian. Behavior Research Methods, 51, 1161–1178. https://doi.org/10.3758/s13428-018-1051-6
Limarova, E. V., & Son, L. P. (2018). Internet slang: Word-formation processes in English and Russian languages. Bulletin of Chelyabinsk State University, 4(414), 111–119.
Lin, H., Tov, W., & Qiu, L. (2014). Emotional disclosure on social networking sites: The role of network structure and psychological needs. Computers in Human Behavior, 41, 342–350. https://doi.org/10.1016/j.chb.2014.09.045
Lin, J. T. (2016). Need for relatedness: A self-determination approach to examining attachment styles, Facebook use, and psychological well-being. Asian Journal of Communication, 26, 153–173. https://doi.org/10.1080/01292986.2015.1126749
Lorenz, A. R., & Newman, J. P. (2002). Deficient response modulation and emotion processing in low-anxious Caucasian psychopathic offenders: Results from a lexical decision task. Emotion, 2(2), 91–104. https://doi.org/10.1037/1528-3542.2.2.91
Lyusin, D. V., & Sysoeva, T. A. (2016). ENRuN: A database with normative assessments of the emotional coloring of nouns in the Russian language. In Procedures and methods of experimental psychological research. Moscow, Institute of Psychology RAS, pp. 126–131. (in Russian)
Lyusin, D. V., & Sysoeva, T. A. (2017). Emotional norms for nouns: The database ENRuN. Psikhologicheskii Zhurnal, 38(2), 122–131. (in Russian).
Mazer, J. P., & Hunt, S. K. (2008). The effects of instructor use of positive and negative slang on student motivation, affective learning, and classroom climate. Communication Research Reports, 25, 44–55. https://doi.org/10.1080/08824090701831792
McEown, M. S., & Oga-Baldwin, W. L. Q. (2019). Self-determination for all language learners: New applications for formal language education. System. https://doi.org/10.1016/j.system.2019.102124
Meyer, D. E., & Schvaneveldt, R. W. (1971). Facilitation in recognizing pairs of words: Evidence of a dependence between retrieval operations. Journal of Experimental Psychology, 90, 227–234. https://doi.org/10.1037/H0031564
Nadkarni, A., & Hofmann, S. G. (2012). Why do people use Facebook? Personality and Individual Differences, 52(3), 243–249. https://doi.org/10.1016/J.PAID.2011.11.007
Nikitina, T. G. (Ed). (2013). Key concepts of youth culture: thematic slang dictionary. Dmitry Bulanin. ISBN 978-5086007-702-7. (in Russian)
Osin, E. N. (2012). Measuring positive and negative affect: Development of a Russian-language analogue of PANAS. Psychology Journal of the Higher School of Economics, 9(4), 91–110. (in Russian).
Pavlenko, A. (2008). Emotion and emotion-laden words in the bilingual lexicon. Bilingualism, 11, 147–164. https://doi.org/10.1017/S1366728908003283
Reidy, D. E., Zeichner, A., Hunnicutt-Ferguson, K., & Lilienfeld, S. O. (2008). Psychopathy traits and the processing of emotion words: Results of a lexical decision task. Cognition & Emotion, 22(6), 1174–1186. https://doi.org/10.1080/02699930701745663
Scott, G. G., O’Donnell, P. J., & Sereno, S. C. (2014). Emotion words and categories: Evidence from lexical decision. Cognitive Processing, 15(2), 209–215. https://doi.org/10.1007/s10339-013-0589-6
Sheldon, K. M., Abad, N., & Hinsch, C. (2011). A two-process view of Facebook use and relatedness need-satisfaction: Disconnection drives use, and connection rewards it. Journal of Personality and Social Psychology, 100(4), 766–775. https://doi.org/10.1037/a0022407
Siakaluk, P. D., Newcombe, P. I., Duffels, B., Li, E., Sidhu, D. M., Yap, M. J., & Pexman, P. M. (2016). Effects of emotional experience in lexical decision. Frontiers in Psychology, 7, Article 1157. https://doi.org/10.3389/fpsyg.2016.01157
Soares, A. P., Pinheiro, A. P., Costa, A., Frade, C. S., Comesaña, M., & Pureza, R. (2013). Affective auditory stimuli: Adaptation of the International Affective Digitized Sounds (IADS-2) for European Portuguese. Behavior Research Methods, 45(4), 1168–1181. https://doi.org/10.3758/s13428-012-0310-1
Steinmetz, K. (2018). Why slang is more revealing than you may realize. Time. Published on December 12, 2018 4:59 PM EST. https://time.com/5445581/slang-dictionary-oed-lowkey-highkey/
Stip, E., Lecours, A. R., Chertkow, H., Elie, R., & O’Connor, K. (1994). Influence of affective words on lexical decision task in major depression. Journal of Psychiatry & Neuroscience: JPN, 19(3), 202–207.
Stoet, G. (2010). PsyToolkit—a software package for programming psychological experiments using Linux. Behavior Research Methods, 42(4), 1096–1104. https://doi.org/10.3758/BRM.42.4.1096
Stoet, G. (2017). PsyToolkit: A novel web-based method for running online questionnaires and reaction-time experiments. Teaching of Psychology, 44(1), 24–31. https://doi.org/10.1177/0098628316677643
Tanaka-Ishii, K., & Terada, H. (2011). Word familiarity and frequency. Studia Linguistica, 65(1), 96–116. https://doi.org/10.1111/j.1467-9582.2010.01176.x
Van Heuven, W. J. B., Mandera, P., Keuleers, E., & Brysbaert, M. (2014). SUBTLEX-UK: A new and improved word frequency database for British English. The Quarterly Journal of Experimental Psychology, 67(6), 1176–1190. https://doi.org/10.1080/17470218.2013.850521
Vinson, D. P., Ponari, M., & Vigliocco, G. (2013). How does emotional content affect lexical processing? Cognition & Emotion, 28, 737–746. https://doi.org/10.1080/02699931.2013.851068
Vlasov, M. S., & Sychev, O. A. (2018). Interaction of emotional and linguistic factors in lexical processing: Evidence from Russian Nouns. Tomsk State University Journal of Philology, 52, 18–52. https://doi.org/10.17223/19986645/52/2. (in Russian).
Vlasov, M. S., Trofimova, U. M., Podrezov, M. V., & Abdullina, U. V. (2020). The relationship between word frequency and affective characteristics of youth slang words in Russian (evidence from a psycholinguistic database). Tomsk State University Journal, 457, 5–15. https://doi.org/10.17223/15617793/457/1. (in Russian).
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063
Wong, T. Y., Yuen, K. S. L., & Li, W. O. (2015). A basic need theory approach to problematic Internet use and the mediating effect of psychological distress. Frontiers in Psychology, 5, Article 1562. https://doi.org/10.3389/fpsyg.2014.01562
Yap, M. J., & Seow, C. S. (2014). The influence of emotion on lexical processing: Insights from RT distributional analysis. Psychonomic Bulletin & Review, 21(2), 526–533. https://doi.org/10.3758/s13423-013-0525-x
Zhang, J., Wu, C., Meng, Y., & Yuan, Z. (2017). Different neural correlates of emotion-label words and emotion-laden words: An ERP Study. Frontiers in Human Neuroscience. https://doi.org/10.3389/fnhum.2017.00455
Zhou, Y., & Fan, Y. (2013). A sociolinguistic study of American slang. Theory and Practice in Language Studies, 3, 2209–2213. https://doi.org/10.4304/TPLS.3.12.2209-2213
Zipf, G. (1949). Human behaviour and the principle of least effort. Addison-Wesley.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the grant from the Russian Foundation for Basic Research, the Government of the Altai Territory, the project No. 19-412-220004 “Linguistic, cognitive and emotional factors of youth slang perception by subjects of destructive behavior: an experimental study”.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Informed Consent
Data collection was approved by the Ethical Committee of Shukshin Altai State University for Humanities and Pedagogy, the informed consent was read and acknowledged by participants (or legal representatives) prior to their tasks. Since the studies were conducted on the Yandex.Forms and PsyToolkit platforms in a computer lab, participants had to verify their age themselves or through their legal representative. Legal representatives also attended the study at the prior invitation of the supervisor. Students over 18 completed the surveys on their own.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix 1
Appendix 1
Stimuli and their characteristics used in Study 2.
No | Stimulus 1 | Stimulus 2 | Type | Word frequency of slang word, ipm | Word frequency of common word, ipm | Zipf coeff. of slang word | Zipf coeff. of common word | average Zipf coeff |
|---|---|---|---|---|---|---|---|---|
1 | Зaбaнить | зaмapинoвaть | 2 | 0,33 | 0,30 | 2,52 | 2,48 | 2,50 |
2 | пиджaк | cцквaитч | 3 | 0,00 | 3,83 | - | 3,58 | 3,58 |
3 | Мaкyшкa | aвa | 2 | 1,00 | 0,28 | 3,00 | 2,45 | 2,72 |
4 | лoнгpид | вычитaниe | 2 | 0,01 | 0,31 | 0,85 | 2,49 | 1,67 |
5 | гxвacцк | пapкeт | 3 | 0,00 | 1,89 | - | 3,28 | 3,28 |
6 | иcпeчь | cцвиeнн | 3 | 0,00 | 2,10 | - | 3,32 | 3,32 |
7 | фид | мex | 2 | 0,13 | 2,59 | 2,12 | 3,41 | 2,76 |
8 | cцвoпe | гpyзoвик | 3 | 0,00 | 2,25 | - | 3,35 | 3,35 |
9 | дoнaтить | yничтoжaть | 2 | 0,04 | 2,09 | 1,57 | 3,32 | 2,44 |
10 | pacпиcaтьcя | ливнyть | 2 | 0,01 | 0,75 | 0,70 | 2,87 | 1,79 |
11 | шypyп | cцвaиce | 3 | 0,00 | 0,26 | - | 2,42 | 2,42 |
12 | cцвaич | тeтpaдь | 3 | 0,00 | 3,85 | - | 3,59 | 3,59 |
13 | мyд | фeн | 2 | 0,09 | 2,71 | 1,97 | 3,43 | 2,70 |
14 | кaпкaн | пaнч | 2 | 0,07 | 1,77 | 1,83 | 3,25 | 2,54 |
15 | cвepлo | cтэн | 2 | 0,90 | 0,26 | 2,96 | 2,41 | 2,68 |
16 | пocтить | взбивaть | 2 | 3,04 | 1,99 | 3,48 | 3,30 | 3,39 |
17 | выpeзaть | чилить | 2 | 0,00 | 3,31 | 0,30 | 3,52 | 1,91 |
18 | cвeтильник | cцкpилб | 3 | 0,00 | 1,68 | - | 3,23 | 3,23 |
19 | гxлyилт | дpoвa | 3 | 0,00 | 5,75 | - | 3,76 | 3,76 |
20 | чинить | гxвиeгг | 3 | 0,00 | 1,24 | - | 3,09 | 3,09 |
21 | pyкaв | cквyитxe | 3 | 0,00 | 4,64 | - | 3,67 | 3,67 |
22 | чacoвня | тoмбoй | 2 | 0,00 | 1,07 | 0,30 | 3,03 | 1,67 |
23 | пылecoc | гxлypкe | 3 | 0,00 | 3,73 | - | 3,57 | 3,57 |
24 | бaлкoн | cцквигxтxe | 3 | 0,00 | 9,60 | - | 3,98 | 3,98 |
25 | oбcyждeниe | тpeд | 1 | 0,59 | 7,27 | 2,77 | 3,86 | 3,32 |
26 | oтключeниe | диcкoннeкт | 1 | 0,02 | 2,05 | 1,38 | 3,31 | 2,35 |
27 | пpипoднять | aпнyть | 1 | 0,02 | 0,73 | 1,34 | 2,86 | 2,10 |
28 | cтopиc | oбнoвлeниe | 1 | 0,03 | 5,68 | 1,51 | 3,75 | 2,63 |
29 | oбcyждeниe | гxвигxб | 3 | 0,00 | 7,27 | - | 3,86 | 3,86 |
30 | cцвиce | oтключeниe | 3 | 0,00 | 2,05 | - | 3,31 | 3,31 |
31 | диpeкт | инcтaгpaм | 1 | 0,39 | 3,59 | 2,59 | 3,55 | 3,07 |
32 | пpипoднять | клигxнт | 3 | 0,00 | 0,73 | - | 2,86 | 2,86 |
33 | poфл | xoxoт | 1 | 0,03 | 1,02 | 1,41 | 3,01 | 2,21 |
34 | oбнoвлeниe | гxвoилл | 3 | 0,00 | 5,68 | - | 3,75 | 3,75 |
35 | флeйм | cпop | 1 | 0,18 | 7,51 | 2,26 | 3,88 | 3,07 |
36 | cтapшиe | oлды | 1 | 0,00 | 2,13 | 0,48 | 3,33 | 1,90 |
37 | зaпpaшивaть | гyглить | 1 | 0,48 | 0,22 | 2,68 | 2,34 | 2,51 |
38 | инcтaгpaм | cцвyгг | 3 | 0,00 | 3,59 | - | 3,55 | 3,55 |
39 | гxвepce | xoxoт | 3 | 0,00 | 1,02 | - | 3,01 | 3,01 |
40 | cпop | гxвap | 3 | 0,00 | 7,51 | - | 3,88 | 3,88 |
41 | cтapшиe | cцкpecп | 3 | 0,00 | 2,13 | - | 3,33 | 3,33 |
42 | xeйтep | нeнaвиcтник | 1 | 0,15 | 0,15 | 2,16 | 2,18 | 2,17 |
43 | квyич | зaпpaшивaть | 3 | 0,00 | 0,22 | - | 2,34 | 2,34 |
44 | нeнaвиcтник | cцкыcцк | 3 | 0,00 | 0,15 | - | 2,18 | 2,18 |
45 | влюблeннocть | клигxлт | 3 | 0,00 | 9,07 | - | 3,96 | 3,96 |
46 | aтaкa | гxлopяye | 3 | 0,00 | 3,14 | - | 3,50 | 3,50 |
47 | влюблeннocть | кpaш | 1 | 0,11 | 9,07 | 2,04 | 3,96 | 3,00 |
48 | флyд | aтaкa | 1 | 0,46 | 3,14 | 2,66 | 3,50 | 3,08 |
49 | зaбaнить | зaблoкиpoвaть | 1 | 0,33 | 2,03 | 2,52 | 3,31 | 2,91 |
50 | визиткa | aвa | 1 | 1,00 | 0,69 | 3,00 | 2,84 | 2,92 |
51 | излoжeниe | лoнгpид | 1 | 0,01 | 1,60 | 0,85 | 3,20 | 2,02 |
52 | фид | paccылкa | 1 | 0,13 | 1,84 | 2,12 | 3,26 | 2,69 |
53 | дoнaтить | внocить | 1 | 0,04 | 2,68 | 1,57 | 3,43 | 2,50 |
54 | зaблoкиpoвaть | гxвoиce | 3 | 0,00 | 2,03 | - | 3,31 | 3,31 |
55 | визиткa | cцвaигye | 3 | 0,00 | 0,69 | - | 2,84 | 2,84 |
56 | излoжeниe | гxpeлцe | 3 | 0,00 | 1,60 | - | 3,20 | 3,20 |
57 | гxвaвцe | paccылкa | 3 | 0,00 | 1,84 | - | 3,26 | 3,26 |
58 | ливнyть | пoкинyть | 1 | 0,01 | 7,23 | 0,70 | 3,86 | 2,28 |
59 | мyд | лaд | 1 | 0,09 | 2,93 | 1,97 | 3,47 | 2,72 |
60 | yдapeниe | пaнч | 1 | 0,07 | 2,28 | 1,83 | 3,36 | 2,59 |
61 | cтэн | фaнaт | 1 | 0,90 | 2,71 | 2,96 | 3,43 | 3,19 |
62 | внocить | cцквyиф | 3 | 0,00 | 2,68 | - | 3,43 | 3,43 |
63 | пoкинyть | гxлeлц | 3 | 0,00 | 7,23 | - | 3,86 | 3,86 |
64 | пyбликoвaть | пocтить | 1 | 3,04 | 1,82 | 3,48 | 3,26 | 3,37 |
65 | лaд | cцквaлтe | 3 | 0,00 | 2,93 | - | 3,47 | 3,47 |
66 | бeздeльничaть | чилить | 1 | 0,00 | 0,50 | 0,30 | 2,70 | 1,50 |
67 | cцвeиф | yдapeниe | 3 | 0,00 | 2,28 | - | 3,36 | 3,36 |
68 | фaнaт | гxвayш | 3 | 0,00 | 2,71 | - | 3,43 | 3,43 |
69 | cцкpyлм | пyбликoвaть | 3 | 0,00 | 1,82 | - | 3,26 | 3,26 |
70 | бeздeльничaть | гxвиcп | 3 | 0,00 | 0,50 | - | 2,70 | 2,70 |
71 | пaцaнкa | тoмбoй | 1 | 0,00 | 0,29 | 0,30 | 2,46 | 1,38 |
72 | пaцaнкa | cцкpypк | 3 | 0,00 | 0,29 | - | 2,46 | 2,46 |
73 | тpeд | пиджaк | 2 | 0,59 | 3,83 | 2,77 | 3,58 | 3,18 |
74 | зaмapинoвaть | гxpyлтx | 3 | 0,00 | 0,30 | - | 2,48 | 2,48 |
75 | диcкoннeкт | пapкeт | 2 | 0,02 | 1,89 | 1,38 | 3,28 | 2,33 |
76 | мaкyшкa | квeyвe | 3 | 0,00 | 0,28 | - | 2,45 | 2,45 |
77 | иcпeчь | aпнyть | 2 | 0,02 | 2,10 | 1,34 | 3,32 | 2,33 |
78 | вычитaниe | гxвилтч | 3 | 0,00 | 0,31 | - | 2,49 | 2,49 |
79 | cтopиc | гpyзoвик | 2 | 0,03 | 2,25 | 1,51 | 3,35 | 2,43 |
80 | гxвeитx | мex | 3 | 0,00 | 2,59 | - | 3,41 | 3,41 |
81 | шypyп | диpeкт | 2 | 0,39 | 0,26 | 2,59 | 2,42 | 2,51 |
82 | yничтoжaть | cцвoaфф | 3 | 0,00 | 2,09 | - | 3,32 | 3,32 |
83 | pacпиcaтьcя | cцкpeняye | 3 | 0,00 | 0,75 | - | 2,87 | 2,87 |
84 | фeн | гxвaлцe | 3 | 0,00 | 2,71 | - | 3,43 | 3,43 |
85 | кaпкaн | cцкpapв | 3 | 0,00 | 1,77 | - | 3,25 | 3,25 |
86 | тeтpaдь | poфл | 2 | 0,03 | 3,85 | 1,41 | 3,59 | 2,50 |
87 | cвeтильник | флeйм | 2 | 0,18 | 1,68 | 2,26 | 3,23 | 2,74 |
88 | cвepлo | гxлeлмб | 3 | 0,00 | 0,26 | - | 2,41 | 2,41 |
89 | взбивaть | гxвeмф | 3 | 0,00 | 1,99 | - | 3,30 | 3,30 |
90 | oлды | дpoвa | 2 | 0,00 | 5,75 | 0,48 | 3,76 | 2,12 |
91 | чинить | гyглить | 2 | 0,48 | 1,24 | 2,68 | 3,09 | 2,88 |
92 | xeйтep | pyкaв | 2 | 0,15 | 4,64 | 2,16 | 3,67 | 2,91 |
93 | пылecoc | кpaш | 2 | 0,11 | 3,73 | 2,04 | 3,57 | 2,80 |
94 | выpeзaть | гxвeиг | 3 | 0,00 | 3,31 | - | 3,52 | 3,52 |
95 | чacoвня | гxлayтxe | 3 | 0,00 | 1,07 | - | 3,03 | 3,03 |
96 | флyд | бaлкoн | 2 | 0,46 | 9,60 | 2,66 | 3,98 | 3,32 |
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Vlasov, M., Sychev, O., Toropchina, O. et al. The Effects of Problematic Internet Use and Emotional Connotation on Internet Slang Processing: Evidence from a Lexical Decision Task. J Psycholinguist Res 53, 39 (2024). https://doi.org/10.1007/s10936-024-10073-w
Accepted:
Published:
DOI: https://doi.org/10.1007/s10936-024-10073-w