Do personal attributes and an understanding of sarcasm and metaphor explain problematic experiences on the Internet? —A survey for the development of information literacy education tools—

Authors

  • Hiroshi Ichikawa Otsuma Women's University
  • Yuhiko TOYODA Sanno University
  • Mika TAKEUCHI Jissen Women’s University
  • Mitsuteru TASHIRO Tama University
  • Masao SUZUKI Waseda University

DOI:

https://doi.org/10.14738/tnc.32.1169

Keywords:

Internet Risk, comprehension of metaphor and sarcasm, theory of mind, educational tool

Abstract

The Internet today provides users with a great amount of convenience due to the improvement of tools and their functions, and the expansion in the numbers of users. However, with the expansion of both online content and time spent online, new and potential risks have emerged in this virtual space. A majority of Japanese students experience communication troubles over the Internet, and therefore higher education institutions have increased their efforts to reduce risks on the Internet by, for example, offering basic security education through information literacy programs. However, because of the number and variability of Internet risks, it is unlikely that these efforts have achieved satisfactory results. As one of the risk factors inducing troubles on the Internet, where users exchange information with other (anonymous) users, we examine the immaturity of the “theory of mind,” which is generally used to infer the conditions, viewpoints, and comprehension level of others.

This study reports the results of a self-report questionnaire used to examine the problems or difficulties encountered on the Internet by young women in Japan. It focuses on the relationship between the comprehension of sarcasm and metaphor expressions, provided for the purpose of estimating the “theory of mind,” as well as of Internet terminology and the problematic experiences. The problems identified were roughly classified into four different categories: addictive Internet use, dishonest/illegal dealings, communication gaps, and shopping-related difficulties. Multiple regression analyses was conducted, aimed at identifying factors that could explain such problems. The results suggested that personal attributes and sensation-seeking tendencies, including social vulnerability and anxiety, and the understanding of sarcasm, metaphor expressions, and Internet terminology, might be significantly correlated with the problems experienced. On the basis of this study, proposals are made as to what areas should be focused on in information literacy education programs in the future.

References

. OECD: THE PROTECTION OF CHILDREN ONLINE: Risks faced by children online and policies to protect themtal Psychology, 14, 19asses of Collective Attention in Twitter. In Proceedings of the 21st International Confere(accessed 2014-12-17)

. Ministry of Internal Affairs and Communications Institute for Information and Communications Policy. Announcement of Issuance of FY2013 Internet Literacy Indicator for Students Etc. http://www.soumu.go.jp/main_content/000175589.pdf(accessed 2014-12-17).

. HIRAI Tomohisa. (2012). Why does "Enjyo" happen on the Web? : An Examination based on Japanese Web Culture, Journal of Information and Communication Research, Vol.29 No.4, 61–71.

. Thurlow, C., Lengel, L., and Tomic, A. (2004). 004e .mic, 18101ification method of Internet related troubles,MT) as a new

. O'Sullivan, P.B. and Flanigan, A.J. (2003). Reconceptualizing 'Flaming' and Other Problematic Messages, New Media & Society, Vol.5 (1): 69–94, SAGE.

. Takeichi, Y., Sasahara,K., Suzuki, R., and Arita,T. (2014). Twitter as Social Sensor: Dynamics and Structure in Major Sporting Events, Artificial Life 14, 778–784.

. Kwak, H., Lee, C., Park, H., and Moon, S. (2010). What is Twitter, a Social Network or a News Media? In Proceedings of the 19th International Conference on World Wide Web, 591–600.

. Bollen, J., Goncalves, B., Ruan, G., and Mao, H. (2011a). Happiness is Assortative in Online Social Networks. Artificial Life, 17(3):237–251.

. Gabowicz, P. A., Ramasco, J. J., Moro, E., Pujol, J. M., and Egu´ıluz, V. M. (2012). Social Features of Online Networks: The Strength of Intermediary Ties in Online Social Media.PLoS ONE, 7(1);e29358

. Conover, M. D., Gonc¸alves, B., Flammini, A., and Menczer, F. (2012). Partisan Asymmetries in Online Political Activity. EPJ Data Science, 1(1):6.

. Romero, D. M., Meeder, B., and Kleinberg, J. (2011). Differencesyrne, & Whiten, A. (Eds.), Machiavellian intelligence: Social expertise and the evolution of intellect in monkeys, apes, and humans. Oxford: Clarendoternational Conference on World Wide Web, 695–704.

. Weng, L., Flammini, A., Vespignani, A., and Menczer, F. (2012). Competition among memes in a world with limited attention. Scientific Reports, 2:335.

. Lehmann, J., Gonc¸alves, B., Ramasco, J. J., and Cattuto, C. (2012). Dynamical Classes of Collective Attention in Twitter. In Proceedings of the 21st International Conference on World Wide Web, 251–260.

. Golder, S. A. and Macy, M.W. (2011). Diurnal and Seasonal Mood Vary with Work, Sleep, and Daylength Across Diverse Cultures. Science, 333(6051):1878–1881.

. Sakaki, T., Okazaki, M., and Matsuo, Y. (2010). Earthquake Shakes Twitter Users: Real-Time Event Detection by Social Sensors. In Proceedings of the 19th International Conference on World Wide Web, 851–860.

. Borge-Holthoefer, J., Rivero, A., Garc´ıa, I., Cauh´e, E., Ferrer, A., Ferrer, D., Francos, D., I˜niguez, D., P´erez, M. P., Ruiz, G., Sanz, F., Serrano, F., Vi˜nas, C., Taranc´on, A., and Moreno, Y. (2011). Structural and Dynamical Patterns on Online Social Networks: The Spanish May 15th Movement as a Case Study. PLoS ONE, 6(8):e23883.

. Gonz´alez-Bail´on, S., Borge-Holthoefer, J., Rivero, A., and Moreno, Y. (2011). The Dynamics of Protest Recruitment through an Online Network. Scientific Reports, 1:197.

. Takahashi, T., Tomioka, R., and Yamanishi, K. (2014). Discovering Emerging Topics in Social Streams via Link-Anomaly Detection. Knowledge and Data Engineering, IEEE Transactions on, 26(1):120–130.

. Bollen, J., Mao, H., and Zeng, X. (2011b). Twitter Mood Predicts the Stock Market. Journal of Computational Science, 2(1):1–8.

. Sasahara, K., Hirata, Y., Toyoda, M., Kitsuregawa, M., and Aihara, K. (2013). Quantifying Collective Attention from Tweet Stream. PLoS ONE, 8(4):e61823.

. Heinrich, HW. 1931. Industrial Accident Prevention. New York: McGraw-Hill.

. Premack, D., & Woodruff, G. (1978). Does the chimpanzee have a theory of mind? The Behavioral and Brain Sciences, 1, 515–526.

. Premack, D. (1988). 'Does the chimpanzee have a theory of mind?' revisited. In R. Byrne, & Whiten, A. (Eds.), Machiavellian intelligence: Social expertise and the evolution of intellect in monkeys, apes, and humans. Oxford: Clarendon Press. 160–179.

. Hobson, R.P. (1993). Autism and the development of mind. Hove: Lawrence Erlbaum Associates.

. Moore, C. (1996). Theories of mind in infancy. British Journal of Developmental Psychology, 14, 19–40.

. Simon Baron-Cohen, Alan M. Leslie, Uta Frith. (1985). Does the autistic child have a “theory of mind” ?, Cognition, Volume 21, Issue 1, 37–46.

. Takamiya, Matsui et al (2009). Brain activation associated with theory of mind: An fMRI study. Journal of Human Environmental Studies Vol. 7 (2009) No. 2 P 129–135.

. Moriguchi, Y. 2011 Psychosomatic medicine and neuroscience on understanding of selves and other's mind. Journal of the Human Arts and Sciences Vol. 7 (2011) No. 1 10–16.

. Adachi, T. (2006). The Study of Situational Recognition of Attention Deficit/Hyperactivity Disorders, Asperger's Disorder and High Functioning Autism with the Metaphor and Sarcasm Scenario Test (MSST), Official Journal of the Japanese Society of Child Neurology 38(3), 177–181, 2006-05-01.

. Takeuchi, M., Suzuki, M. (2000). The basic study of the Self Risk Management Test (SRMT) as a new tool for the educational programs informing lifetime risks of swindling victimization, Sanno College Junior Bulletin, Vol.33, 11–24.

. Maslow, A.H. (1954). Motivation and Personality, Harper & Row, NY.

. Cloninger, C.R. (1987). A systematic method for clinical description and classification of personality varients: a proposal. Arch. Gen. Psychiat., 44, 573–588.

. Tashiro, M. (2011). Proposal of classification method of Internet related troubles, The Infosocionomics Society Vol.6, No.1, 101–114, 2011-6-18.

Downloads

Published

2015-05-02

How to Cite

Ichikawa, H., TOYODA, Y., TAKEUCHI, M., TASHIRO, M., & SUZUKI, M. (2015). Do personal attributes and an understanding of sarcasm and metaphor explain problematic experiences on the Internet? —A survey for the development of information literacy education tools—. Discoveries in Agriculture and Food Sciences, 3(2), 158. https://doi.org/10.14738/tnc.32.1169