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Emotionality of Turkish language and primary adaptation of affective English norms for Turkish

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Abstract

Emotional load assessment of the written words has gained considerable interest in psycholinguistics, semantics, and analysis of psychophysiological and electrophysiological correlates of emotional processing. Considering the lack of a publicly available database with affective ratings of contemporary verbal stimuli obtained from native Turkish speakers, we present the affective norms for two datasets of Turkish words carefully adapted from the Affective Norms for English Words (ANEW) database. The valence and arousal ratings are obtained from 61 college-aged participants for 127 highly arousing, emotionally-loaded words in the Adapted Turkish Affective List (ATAL). The ATAL ratings show a tendency of classifying fewer words as positive compared to the original list of stimuli, significantly higher arousal levels for positively rated Turkish stimuli compared to the negative and neutral words, and more congruence in arousal levels of positively exciting words. For the medium to high arousing 508 words in the Expanded Turkish Affective List (ETAL) that cover the whole 9-point spectrum of the valence dimension, 136 Turkish respondents from a wider age, education, and occupation background show higher excitability towards highly unpleasant words. Strong cross-linguistic correlations of + 0.968 between the valence ratings of ANEW and ATAL and + 0.878 for ANEW and ETAL demonstrate the ease of transferring and perceiving the valence levels across English and Turkish. The medium correlation of roughly + 0.450 between the English and Turkish arousal ratings account for lower excitation levels perceived by the native Turkish speakers and indicate the arousal dimension is similar to familiarity and originality in exhibiting more variations between different cultures. These findings demonstrate that this expanded database of partial affective normative ratings can be used as the ground truth for emotional and neurocognitive assessments, and that the presented methodology can be utilized for developing a comprehensive Turkish affective lexicon. The utilized word selection criteria also enable a cross-cultural analysis of adapted words in Turkish and other languages. Detailed normative ratings of this Turkish adaptation are included in the supplementary materials.

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Notes

  1. http://www.turesdatabase.com

  2. After completion of experiments and during the revision process, we were notified of a study on Turkish emotional word norms by Kapucu et al. (2018) who have obtained ratings for valence and arousal dimensions and five discrete emotions of 2,031 Turkish words. We compare our findings with theirs in the “Discussion” section.

  3. https://tscorpus.com/corpora/ts-corpus-v2

  4. http://79.123.177.209/hasim/langres/BounWebCorpus.tgz

  5. https://www.qualtrics.com/research-core/

References

  • Ayçiceği, A., & Harris, C. (2004). BRIEF REPORT: Bilinguals’ recall and recognition of emotion words. Cognition and Emotion, 18(7), 977–987.

    Article  Google Scholar 

  • Aydın Oktay, E., Balcı, K., Salah, A.A. (2015). Automatic assessment of dimensional affective content in Turkish multi-party chat messages. In Proceedings of the international workshop onemotion representations and modelling for companion technologies (pp. 19–24).

  • Aydin, C. (2018). The differential contributions of visual imagery constructs on autobiographical thinking. Memory, 26(2), 189–200. https://doi.org/10.1080/09658211.2017.1340483.

    Article  PubMed  Google Scholar 

  • Bailey, K., & Chapman, P. (2012). When can we choose to forget? An ERP study intoitem-method directed forgetting of emotional words. Brain and Cognition, 78(2), 133–147.

    Article  PubMed  Google Scholar 

  • Beck, T.W. (2013). The importance of a priori sample size estimation in strength and conditioning research. The Journal of Strength & Conditioning Research, 27(8), 2323–2337.

    Article  Google Scholar 

  • Bloom, L. (1998). Language development and emotional expression. Pediatrics, 102(Supplement E1), 1272–1277.

    PubMed  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • Bradley, M.M., & Lang, P.J. (1999). Affective norms for English words (ANEW): Instruction manual and affective ratings (Tech. Rep.). Technical Report C-1, the Renter for Research in Psychophysiology, University of Florida.

  • Bradley, M. M., & Lang, P. J. (2010). Affective norms for English words (ANEW): Instruction manual and affective ratings (Tech. Rep.). Technical Report C-2, the Center for Research in Psychophysiology, University of Florida.

  • Çakmak, O., Kazemzadeh, A., Yıldırım, S., Narayanan, S. (2012). Using interval type-2 fuzzy logic to analyze Turkish emotion words. In Signal & information processing association annualsummit and conference (apsipa asc), 2012 asia-pacific (pp. 1–4).

  • Chanel, G., Kronegg, J., Grandjean, D., Pun, T. (2006). Emotion assessment: Arousal evaluation using EEG and peripheral physiological signals. Multimedia Content Representation, Classification and Security, 530–537.

  • Citron, F.M.M. (2012). Neural correlates ofwritten emotion word processing: A review of recent electrophysiological and hemodynamic neuroimaging studies. Brain and Language, 122(3), 211–226.

    Article  PubMed  Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences. NJ: Lawrence Earlbaum Associates, 2. ISBN 978-0805802832.

  • Cross, S.E., Hardin, E.E., Gercek-Swing, B. (2011). The what, how, why, and where of self-construal. Personality and Social Psychology Review, 15(2), 142–179. https://doi.org/10.1177/1088868310373752.

    Article  PubMed  Google Scholar 

  • Degner, J., Doycheva, C., Wentura, D. (2012). It matters how much you talk: On the automaticity of affective connotations of first and second language words. Bilingualism: Language and Cognition, 15(1), 181–189.

    Article  Google Scholar 

  • Eilola, T.M., & Havelka, J. (2010). Affective norms for 210 British English and Finnish nouns. Behavior Research Methods, 42(1), 134–140.

    Article  PubMed  Google Scholar 

  • Fontaine, J.R., Scherer, K.R., Roesch, E.B., Ellsworth, P.C. (2007). The World of Emotions Is Not. Psychological science, 18(12), 1050–1057. https://doi.org/10.1111/j.1467-9280.2007.02024.x.

    Article  PubMed  Google Scholar 

  • Ford, B.Q., & Mauss, I.B. (2015). Culture and emotion regulation (Vol. 3).

  • Gilet, A.L., Gru̇hn, D., Studer, J., Labouvie-Vief, G. (2012). Valence, arousal, and imagery ratings for 835 French attributes by young, middle-aged, and older adults: The French Emotional Evaluation List (FEEL). Revue Europé,enne de Psychologie Appliquée/European Review of Applied Psychology, 62(3), 173–181.

    Article  Google Scholar 

  • Gökçay, D. (2011). Emotional axes: Psychology, psychophysiology and neuroanatomical correlates. In Affective computing and interaction: Psychological, cognitive and neuroscientific perspectives (pp. 56–73). IGI Global.

  • Gökçay, D., & Smith, M.A. (2008). TÜDADEN:Türkçede Duygusal veAnlamsal Değerlendirmeli Norm Veri Tabanı. In Brain-computer workshop (p. 4).

  • Gomes, C.F.A., Brainerd, C.J., Stein, L.M. (2013). Effects of emotional valence and arousal on recollective and nonrecollective recall. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39(3), 663.

    PubMed  Google Scholar 

  • Gru̇hn, D., & Smith, J. (2008). Characteristics for 200 words rated by young and older adults: Age-dependent evaluations of German adjectives (AGE). Behavior Research Methods, 40(4), 1088–1097.

    Article  PubMed  Google Scholar 

  • Göz, I., Tekcan, A.İ., Erciyes, A.A. (2017). Subjective age-of-acquisition norms for 600 Turkish words from four age groups. Behavior Research Methods, 49(5), 1736–1746. https://doi.org/10.3758/s13428-016-0817-y.

    Article  PubMed  Google Scholar 

  • Halfon, S., Aydın Oktay, E., Salah, A. (2016). A Assessing affective dimensions of play in psychodynamic child psychotherapy via text analysis. In International workshop on human behavior understanding (pp. 15–34).

  • Harris, C.L., Ayçiceği, A., Gleason, J.B. (2003). Taboo words and reprimands elicit greater autonomic reactivity in a first language than in a second language. Applied Psycholinguistics, 24(4), 561–579.

    Article  Google Scholar 

  • Hinojosa, J.A., Mėndez-Bėrtolo, C., Pozo, M.A. (2010). Looking at emotional words is not the same as reading emotional words: {Behavioral} and neural correlates. Psychophysiology, 47(4), 748–757.

    PubMed  Google Scholar 

  • Hofstede, G. (1984). Culture’s consequences: International differences in work-related values. SAGE.

  • Imbir, K.K. (2015). Affective norms for 1,586 Polish words (ANPW): Duality-of-mind approach. Behavior Research Methods, 47(3), 860–870.

    Article  PubMed  Google Scholar 

  • Imbir, K.K. (2016). Affective norms for 4900 Polish words reload (ANPW_R): assessments for valence, arousal, dominance, origin, significance, concreteness, imageability and, age of acquisition. Frontiers in Psychology, 7, 1081. https://doi.org/10.3389/fpsyg.2016.01081.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kacen, J.J., & Lee, J.A. (2002). The influence of culture on consumer impulsive buying behavior. Journal of Consumer Psychology, 12(2), 163–176. https://doi.org/10.1207/153276602760078686.

    Article  Google Scholar 

  • Kapucu, A., Kılıç, A., Özkılıç-Kartal, Y., Sarıbaz, B. (2018). Turkish emotional word norms for arousal, valence, and discrete emotion categories. Psychological Reports, 0(0), 1–22. https://doi.org/10.1177/0033294118814722.

    Google Scholar 

  • Kaviani, H., Sagan, O., Pournaseh, M. (2015). Emotion-Related Words in Persian Dictionaries: Culture, Meaning and Emotion Theory. International Journal of Linguistics, Literature and Culture, 2(3), 1–11.

    Google Scholar 

  • Kloumann, I.M., Danforth, C.M., Harris, K.D., Bliss, C.A., Dodds, P.S. (2012). Positivity of the English language. PloS One, 7(1), e29484.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kroupi, E., Yazdani, A., Ebrahimi, T. (2011). EEG correlates of different emotional states elicited during watching music videos. Affective Computing and Intelligent Interaction, 457–466.

  • Lang, P.J. (1980). Behavioral treatment and bio-behavioral assessment: Computer applications. Technology in Mental Health Care Delivery Systems, 119–137.

  • Lim, N. (2016). Cultural differences in emotion: differences inemotional arousal level between the East and the West. Integrative Medicine Research, 5(2), 105–109. http://linkinghub.elsevier.com/retrieve/pii/S2213422016300191. https://doi.org/10.1016/j.imr.2016.03.004.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lu, L., & Gilmour, R. (2004). Culture and conceptions of happiness: Individual oriented and social oriented SWB. Journal of Happiness Studies, 5(3), 269–291.

    Article  Google Scholar 

  • Luu, S., & Chau, T. (2008). Decoding subjective preference from single-trial near-infrared spectroscopy signals. Journal of Neural Engineering, 6(1), 16003.

    Article  Google Scholar 

  • Markus, H.R., & Kitayama, S. (1991). Culture and the Self - Implications for Cognition, Emotion, and Motivation. Psychology and Review, 98(2), 224–253. https://doi.org/10.1037/0033-295x.98.2.224.

    Article  Google Scholar 

  • Mokhlesin, M., Ahadi, H., Bakhtiari, J., Ahmadizadeh, Z., Kasbi, F. (2015). Persian norms for affective dimensions and lexico semantic features of words. Koomesh, 17(1), 60–76.

    Google Scholar 

  • Montefinese, M., Ambrosini, E., Fairfield, B., Mammarella, N. (2014). The adaptation of the affective norms for English words (ANEW) for Italian. Behavior Research Methods, 46(3), 887–903.

    Article  PubMed  Google Scholar 

  • Moors, A., De Houwer, J., Hermans, D., Wanmaker, S., Van Schie, K., Harmelen, Van, Brysbaert, A.L.M. (2013). Norms of valence, arousal, dominance, and age of acquisition for 4,300Dutch words. Behavior Research Methods, 45(1), 169–177.

    Article  PubMed  Google Scholar 

  • Nicolaou, M.A., Gunes, H., Pantic, M. (2011). Continuous prediction of spontaneous affect from multiple cues and modalities in valence-arousal space. IEEE Transactions on Affective Computing, 2(2), 92–105.

    Article  Google Scholar 

  • Nigg, J.T., & Casey, B.J. (2005). An integrative theory ofattention-deficit/hyperactivity disorder based on the cognitive and affective neurosciences. Development and Psychopathology, 17(3), 785–806.

    Article  PubMed  Google Scholar 

  • Oflazoğlu, Ç, & Yıldırım, S. (2013). Recognizing emotion from Turkish speech using acoustic features. EURASIP Journal on Audio, Speech, and Music Processing, 2013(1), 26.

    Article  Google Scholar 

  • Opitz, B., & Degner, J. (2012). Emotionality in a second language: It’s a matter of time. Neuropsychologia, 50(8), 1961–1967.

    Article  PubMed  Google Scholar 

  • Passarotti, A.M., Sweeney, J.A., Pavuluri, M.N. (2010). Differentialengagement of cognitive and affective neural systems in pediatric bipolar disorder and attention deficit hyperactivity disorder. Journal of the International Neuropsychological Society, 16(1), 106–117.

    Article  PubMed  Google Scholar 

  • Patrick, R.E., Kiang, M., Christensen, B.K. (2015). Neurophysiologicalcorrelates of emotional directed-forgetting in persons with Schizophrenia: An event-related brain potential study. International Journal of Psychophysiology, 98(3), 612–623.

    Article  PubMed  Google Scholar 

  • Paulmann, S., Bleichner, M., Kotz, S.A. (2013). Valence, arousal, and task effects in emotional prosody processing. Frontiers in Psychology, 4, 345. https://doi.org/10.3389/fpsyg.2013.00345.

    Article  PubMed  PubMed Central  Google Scholar 

  • Pietro, C., Silvia, S., Giuseppe, R. (2014). The pursuit of happiness measurement: A psychometric model based on psychophysiological correlates. The Scientific World Journal, 2014.

  • Redondo, J., Fraga, I., Padrȯn, I., Comesaṅa, M. (2007). The Spanish adaptation of ANEW (affective norms for English words). Behavior Research Methods, 39(3), 600–605.

    Article  PubMed  Google Scholar 

  • Riegel, M., Wierzba, M., Wypych, M., żurawski, Ł., Jednorȯg, K., Grabowska, A., Marchewka, A. (2015). Nencki affective word list (NAWL): The cultural adaptation of the Berlin affective word list–reloaded (BAWL-R) for Polish. Behavior Research Methods, 47(4), 1222–1236.

    Article  PubMed  PubMed Central  Google Scholar 

  • Schacht, A., & Sommer, W. (2009). Time course and task dependence of emotion effects in word processing. Cognitive, Affective, and Behavioral Neuroscience, 9(1), 28–43.

    Article  Google Scholar 

  • Sezer, T., & Sezer, B.S. (2013). TS Corpus: Herkes için Türkçe derlem. In Proceedings of the 27th national linguistics conference. antalya. hacettepe university, linguistics department (pp. 217–225).

  • Sheldon, S., Amaral, R., Levine, B. (2017). Individual differences in visual imagery determine how event information is remembered. Memory, 25(3), 360–369. https://doi.org/10.1080/09658211.2016.1178777.

    Article  PubMed  Google Scholar 

  • Soares, A.P., Comesaṅa, M., Pinheiro, A.P., Simȯes, A., Frade, C.S. (2012). The adaptation of the Affective Norms for English words (ANEW) forEuropean Portuguese. Behavior Research Methods, 44(1), 256–269.

    Article  PubMed  Google Scholar 

  • Sylvester, T., Braun, M., Schmidtke, D., Jacobs, A.M. (2016). The Berlin affective word list for children (kidBAWL): exploring processing of affective lexical semantics in the visual and auditory modalities. Frontiers in Psychology, 7, 969. https://doi.org/10.3389/fpsyg.2016.00969.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sze, W.P., Liow, S.J.R., Yap, M.J. (2014). The Chinese Lexicon Project: A repository of lexical decision behavioral responses for 2,500 Chinese characters. Behavior Research Methods, 46(1), 263–273.

    Article  PubMed  Google Scholar 

  • Toglia, M.P., & Battig, W.F. (1978). Handbook of semantic word norms. Lawrence Erlbaum.

  • Trimmer, P.C., Paul, E.S., Mendl, M.T., McNamara, J.M., Houston, A.I. (2013). On the evolution and optimality of mood states. Behavioral Sciences, 3(3), 501–521.

    Article  PubMed  PubMed Central  Google Scholar 

  • Tsai, J.L., Louie, J.Y., Chen, E.E., Uchida, Y. (2007). Learning what feelings to desire: Socialization of ideal affect through children’s storybooks. Personality and Social Psychology Bulletin, 33(1), 17–30. https://doi.org/10.1177/0146167206292749.

    Article  PubMed  Google Scholar 

  • Uchida, Y., & Kitayama, S. (2009). Happiness and unhappiness in east and west: themes and variations. Emotion, 9(4), 441.

    Article  PubMed  Google Scholar 

  • Vecchiato, G., Cherubino, P., Maglione, A.G., Ezquierro, M.T.H., Marinozzi, F., Bini, F., Babiloni, F. (2014a). How to measure cerebral correlates of emotions in marketing relevanttasks. Cognitive Computation, 6 (4), 856–871.

    Article  Google Scholar 

  • Vecchiato, G., Toppi, J., Maglione, A.G., Olejarczyk, E., Astolfi, L., Mattia, D, Babiloni, F. (2014b). Neuroelectrical correlates of trustworthiness and dominance judgments related to the observation of political candidates. Computational and Mathematical Methods in Medicine.

  • Vȯ, M.L.H., Conrad, M., Kuchinke, L., Urton, K., Hofmann, M.J., Jacobs, A.M. (2009). The Berlin affective word list reloaded (BAWL-R). Behavior Research Methods, 41(2), 534–538.

    Article  PubMed  Google Scholar 

  • Wang, Y., Qu, C., Luo, Q., Qu, L., Li, X. (2014). Like or Dislike? Affective Preference Modulates Neural Responseto Others’ Gains and Losses. PloS One, 9(8), e105694.

    Article  PubMed  PubMed Central  Google Scholar 

  • Warriner, A.B., Kuperman, V., Brysbaert, M. (2013). Norms of valence, arousal, and dominance for 13,915 English lemmas. Behavior Research Methods, 45(4), 1191–1207.

    Article  PubMed  Google Scholar 

  • Yılmaz, B., Korkmaz, S., Arslan, D.B., Gu̇ngȯr, E., Asyalı, M.H. (2014). Like/dislike analysis using EEG: Determination of most discriminative channels and frequencies. Computer Methods and Programs in Biomedicine, 113(2), 705–713.

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors would like to thank Dr. Achille Pasqualotto from the Psychology Program at Sabanci University for his helpful suggestions regarding the web-based survey design and for arranging his students’ participation in the experiments. The authors also extend their gratitude to all the participants and researchers in Turkey and abroad who enthusiastically devoted their time to attend the data collection sessions, and to Dr. Huseyin Ozkan for sharing his comments on the initial version of this manuscript. The first author also thanks Mr. Mostafa Mehdipour Ghazi for his inspiring discussions on the role of native and acquired languages in emotional perception.

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Authors and Affiliations

  1. Signal Processing and Information Systems Laboratory, Faculty of Engineering and Natural Sciences, Sabanci University, Tuzla, 34956, Istanbul, Turkey

    Mastaneh Torkamani-Azar, Sumeyra Demir Kanik, Ayse Tuba Vardan & Mujdat Cetin

  2. Sheldon B. Lubar School of Business, University of Wisconsin-Milwaukee, Milwaukee, WI, USA

    Ayse Tuba Vardan

  3. Psychology Program, Faculty of Arts and Social Sciences, Sabanci University, Istanbul, Turkey

    Cagla Aydin

  4. Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA

    Mujdat Cetin

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  1. Mastaneh Torkamani-Azar
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Torkamani-Azar, M., Kanik, S.D., Vardan, A.T. et al. Emotionality of Turkish language and primary adaptation of affective English norms for Turkish. Curr Psychol 38, 273–294 (2019). https://doi.org/10.1007/s12144-018-0119-x

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