Linguistic Cues of Deception in Malaysian Online Investment Scams’ Promotional Materials

Authors

DOI:

https://doi.org/10.17576/gema-2023-2304-09

Keywords:

Deception, Linguistic Cues, Online Investments, Promotional Materials, Scams

Abstract

The entire world has transitioned to a borderless information flow in this high-technology era, making communication more effective at the ease of the fingertips. However, these advantages come with various cybercrimes that can easily mislead readers and win them over to their point of view, including online investment scams. This quantitative study aims to analyse the linguistic cues of deception of investment scams’ promotional materials using the Linguistic Inquiry and Word Count (LIWC) and Statistical Package for Social Science (SPSS) software. The data was gleaned from official website pages of investment scams provided by the Royal Malaysia Police (RMP), Central Bank of Malaysia (CBM), Financial Consumer Alert List (FCA), and the Securities Commission Malaysia (SC). Descriptive analysis and Pearson correlation analysis were conducted. The findings of the descriptive analysis show that the highest linguistic cue used in the online investment scam is Lifestyle. For Pearson correlation analysis, the findings show that linguistic cue for Perception significantly correlates with other linguistic cues such as Lifestyle, Social Process, Cognition, and Affect. This indicates that the linguistic cues used in online investment scams are related. The findings of the study can be used as a guide to prevent online investment scam problems in the future. 

Author Biographies

Ameiruel Azwan Ab Aziz, Universiti Teknologi MARA Cawangan Melaka

Ameiruel Azwan Ab Aziz is a senior lecturer at the Academy of Language Studies, Universiti Teknologi MARA. His research interests include teaching English as a second language (TESL), psychology of language teachers, and forensic linguistic analysis. He has published his work extensively in reputable journals, both locally and internationally.

Nurul Atiqah Mohd Sharif, Universiti Teknologi MARA Cawangan Melaka

Nurul Atiqah Mohd Sharif (MA) is a postgraduate student of Masters in Applied Language Studies currently in her Semester 2 at the Academy of Language Studies, Universiti Teknologi MARA (UiTM), Melaka. Her research interests are in the area of semantics and morphology.

Wan Farah Wani Wan Fakhruddin, Universiti Teknologi Malaysia

Wan Farah Wani Wan Fakhruddin is a Senior Lecturer in the Faculty of Social Sciences and Humanities at Universiti Teknologi Malaysia. Her research interests include a functional approach to language and discourse studies, with an emphasis on professional and academic genres from a Systemic Functional Linguistics perspective.

Amirah Mohd Juned, Universiti Teknologi MARA Cawangan Melaka

Amirah Mohd Juned is a lecturer at UiTM Cawangan Melaka. She obtained her Doctor of Philosophy (Education) from Universiti Teknologi MARA, Shah Alam. Her research interest is in the area of motivation, teacher instructional practices and educational psychology.

Nursyaidatul Kamar Md Shah, Universiti Teknologi MARA Cawangan Melaka

Nursyaidatul Kamar Md Shah is an accomplished English language lecturer at the Academy of Language Studies, UiTM Melaka. With a strong passion for applied linguistics, language studies, and psycholinguistics, she is currently dedicated to pursuing her Ph.D. in applied language studies to further contribute to the field.

Ariff Imran Anuar Yatim, Universiti Teknologi MARA Cawangan Melaka

Ariff Imran Anuar Yatim is a lecturer at the Academy of Language Studies, University Teknologi MARA (UiTM) Melaka, Malaysia. He has a Bac. of Edu (Hons.) in TESL from UiTM and a Master of Applied Linguistics from Universiti Putra Malaysia. His research interests include communication strategies, semantics, and pragmatics.

Aminabibi Saidalvi, Universiti Teknologi MARA Cawangan Johor

Aminabibi Saidalvi was an Associate Professor at the Academy of Language Studies, Universiti Teknologi MARA Johor (UiTM), Pasir Gudang Campus, until June 12, 2023. Her research interests include TESL, Online Integrated Language Learning, Oral Communication Skills, and Second Language Research. 

References

Addawood, A., Badawy, A., Lerman, K., & Ferrara, E. (2019). Linguistic Cues to Deception: Identifying Political Trolls on Social Media. Proceedings of the International AAAI Conference on Web and Social Media, 13(01), 15-25. https://doi.org/10.1609/icwsm.v13i01.3205

Adha, A. (2020). Linguistic Based Cues in Detecting Deception in Indonesian Language Use. Argumentum (1787-3606), (16). https://doi.org/10.34103/argumentum/2020/2

Boyd, R. L., Ashokkumar, A., Seraj, S., & Pennebaker, J. W. (2022). The development and psychometric properties of LIWC-22. Austin, TX: University of Texas at Austin. https://www.liwc.app

Bukit Aman says investment fraud cases surged in 2021, losses exceed RM420m. (2022, January 5). Malay Mail. Retrieved from https://www.malaymail.com/news/malaysia/2022/01/05/bukit-aman-says-investment-fraud-cases-surged-in-2021-losses-exceed-rm420m/2033251

Central Bank of Malaysia (2023). Retrieved from https://www.bnm.gov.my//financial-consumer-alert-list

Choudhury, F. (2014). Can language be useful in detecting deception? The linguistic markers of deception in the Jodi Arias interview.„. Journal of Undergraduate Research, 7(2), 78-92.

Connell, C. (2012). Linguistic Cues to Deception (Doctoral dissertation, Virginia Tech). Retrieved from https://vtechworks.lib.vt.edu/handle/10919/32465

Deora, R. S., & Chudasama, D. (2021). Brief study of cybercrime on the internet. Journal of communication engineering & Systems, 11(1), 1-6. https://doi.org/10.37591/JoCES

DePaulo, B. M., Lindsay, J. J., Malone, B. E., Muhlenbruck, L., Charlton, K., & Cooper, H. (2003). Cues to deception. Psychological Bulletin, 129(1), 74–118. https://doi.org/10.1037/0033-2909.129.1.74

Frankel, T. (2012). The Ponzi scheme puzzle: A history and analysis of con artists and victims. Oxford University Press.

Fuller, C. M., Biros, D. P., & Wilson, R. L. (2009). Decision support for determining veracity via linguistic-based cues. Decision Support Systems, 46(3), 695-703.

Genao, D. R. (2021). Identification of Fraudulent Financial Statements: The Detection of Deception and Collusion in Earnings Calls (Doctoral dissertation, Northcentral University). Retrieved from ProQuest Dissertation https://www.proquest.com/docview/2551555139?pqorigsite=gscholar&fromopenview=true

John, S. (2018, September 18). CNBC. Retrieved from Religious-based financial fraud is rampant. Here’s how to fight it: https://www.cnbc.com/2018/09/06/religious-based-financial-fraud-is-rampant-heres-how-to-fight-it.html

Karim, N. A., Ab Wahid, Z., Ariffin, S. N. K., Nor, S. H. S., Nazlan, A. N., & Kassim, S. (2023). Financial Literacy among University Students and its Implications towards Financial Scams. Information Management and Business Review, 15(3 (I)), 124-128.

Levitan, S. I., Maredia, A., & Hirschberg, J. (2018, June). Linguistic cues to deception and perceived deception in interview dialogues. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) (pp.

-1950).

Li, L., Lee, K. Y., Lee, M., & Yang, S.-B. (2020). Unveiling the cloak of deviance: Linguistic cues for psychological processes in fake online reviews. International Journal of Hospitality Management, 87, 102468. https://doi.org/10.1016/j.ijhm.2020.102468

Mihalcea, R., & Strapparava, C. (2009, August). The lie detector: Explorations in the automatic recognition of deceptive language. In Proceedings of the ACL-IJCNLP 2009 conference short papers (pp. 309-312).

Mohd Padil, H., Kasim, E. S., Muda, S., Ismail, N., & Md Zin, N. (2021). Financial literacy and awareness of investment scams among university students. Journal of Financial Crime, 29(1), 355-367. https://doi.org/10.1108/jfc-01-2021-0012

Naksawat, C., Akkakoson, S., & Loi, C. K. (2016). Persuasion strategies: use of negative forces in scam e-mails. GEMA Online Journal of Language Studies, 16(1), 1-17.

New Straits Times. (2022, August 4). RM5.2b in losses through online scams since 2020. Kuala Lumpur, Malaysia. Retrieved from https://www.nst.com.my/news/crime-courts/2022/08/819331/rm52b-losses-through-online-scams-2020

Newman M. L., Pennebaker J. W., Berry D. S., Richards J. M. (2003). Lying words: Predicting deception from linguistic style. Personality and Social Psychology Bulletin, 29, 665–675. https://doi.org/10.1177/0146167203029005010

Pennebaker, J. W., & King, L. A. (1999). Linguistic styles: language use as an individual difference. Journal of personality and social psychology, 77(6), 1296.

Pennebaker, J. W., Boyd, R. L., Jordan, K., & Blackburn, K. (2015). The development and psychometric properties of LIWC2015.

Rahman, A. A., Azmi, R., & Mohd Yusof, R. (2020). Get-Rich Quick scheme: Malaysian current legal development. Journal of Financial Crime, 28(1), 49-59.

Rubin, V. L., & Conroy, N. J. (2011). Challenges in automated deception detection in computer‐mediated communication. Proceedings of the American Society for Information Science and Technology, 48(1), 1-4.

Schillermann, M. K. (2018). Early detection and prevention of corporate financial fraud (Doctoral dissertation, Walden University).

Securities Commission Malaysia (2020). Annual Report 2020. Retrieved October 19, 2023, from https://www.sc.com.my/api/documentms/download.ashx?id=e1c7eb21-53db-4f02-a8f8-55dc09f9fff

Shaari, A. H., Kamaluddin, M. R., Fauzi, W. F. P., & Mohd, M. (2019). Online-dating romance scam in Malaysia: An analysis of online conversations between scammers and victims. GEMA Online Journal of Language Studies, 19(1), 97-115

Toma, C. L., & Hancock, J. T. (2010, February). Reading between the lines: linguistic cues to deception in online dating profiles. In Proceedings of the 2010 ACM conference on Computer supported cooperative work (pp. 5-8). https://doi.org/10.1145/1718918.171892

Van Der Zee, S., Poppe, R., Havrileck, A., & Baillon, A. (2020). A Personal Model of Trumpery: Linguistic Deception Detection in a Real-World High-Stakes Setting. Psychological Science, 33(1), 3–17. https://doi.org/10.1177/09567976211015941

Zhou, X., & Zafarani, R. (2020). A survey of fake news: Fundamental theories, detection methods, and opportunities. ACM Computing Surveys (CSUR), 53(5), 1-40. https://doi.org/10.1145/3395046

Zhou, L., & Zhang, D. (2008). Following linguistic footprints: Automatic deception detection in online communication. Communications of the ACM, 51(9), 119-122.

Downloads

Additional Files

Published

2023-11-17

Issue

Vol. 23 No. 4 (2023): November 2023

Section

Special Section

License

If the article is accepted for publication, copyright of this article will be vested to UKM Press, National University of Malaysia (UKM).

All articles published in this journal are licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license, unless otherwise stated.