Billions of web searches are recorded every day; however, little is known about the types of financial information that users search for. While many studies have investigated information exchanges in financial forums, this is the first study to identify the financial information needs of Internet users in Malaysia through an analysis of search queries. We identified financial topics and discovered subtopics of interest using text mining. We found that topics with high search volume were related to financial products and services, and very little was related to concepts and information that would increase financial knowledge. The results of this study can be used to develop more strategic online financial education content that not only meets users’ financial information needs but also increases their financial knowledge, especially when the financial knowledge of the global population has remained low over the years.
BehrmanJRMitchellOSSooCK, et al. The effects of financial education and financial literacy: how financial literacy affects household wealth accumulation. Am Econ Rev2012; 102: 300–304.
7.
LusardiAMitchellOS. The economic importance of financial literacy: theory and evidence. J Econ Liter Am Econ Assoc2014; 52: 5–44.
8.
AbreuMMendesV. Financial literacy and portfolio diversification. Quant Finance2010; 10: 515–528.
ChangYDengH. Query understanding for search engines. New York: Springer, 2020.
13.
QiuJXFaulknerACanAE. Towards theme detection in personal finance questions. In: ML In Finance (KDD-MLF ’21). New York: Association for Computing Machinery, 2021, https://discovery.kpi.ua/Record/arxiv.110.01550
AltfestL. Personal financial planning: origins, developments and a plan for future direction. Am Econom2004; 48: 53–60.
17.
GarmanETForgueRE. Personal Finance. 13th ed.Boston, MA: Cengage Learning, 2018.
18.
DouZGuoJ. Query intent understanding. In: ChangYDengH (eds) Query understanding for search engines. New York: Springer, 2020, pp. 69–101.
19.
GuoJLanY. Query classification. In: ChangYDengH (eds) Query understanding for search engines. New York: Springer, 2020, pp. 15–41.
20.
BroderAZ. A taxonomy of web search. ACM SIGIR Forum2002; 36: 3–10.
21.
RoseDELevinsonD. Understanding user goals in web search. In: Thirteenth international World Wide Web conference proceedings, 17–20 May 2004, pp. 13–19. New York: ACM.
22.
Baeza-YatesRCalderón-BenavidesLGonzález-CaroC. The intention behind web queries. Lec Note Comput Sci2006; 4209: 98–109.
23.
JansenBJBoothDLSpinkA. Determining the informational, navigational, and transactional intent of web queries. Inf Process Manag2008; 44: 1251–1266.
24.
ChurchKSmythB. Understanding the intent behind mobile information needs. In: International conference on intelligent user interfaces, proceedings IUI, 8–11 February 2009, pp. 247–256. New York: ACM.
KarpenkoVMukhinKRybakovaD, et al. A study of personal finance practices. The case of online discussions on Reddit. CEUR Workshop Proc2021; 3090: 206–211.
27.
VaalerAReiterLFaulknerAE. They seek, but do they find? Investigating the financial information-seeking behavior of college students. Coll Res Libr2021; 82: 267–285.
ErsoyMAUlcayMErsoyHT. Health information-seeking behaviors about attention deficit hyperactivity disorder on the internet and the analysis of top-ranking websites. Klinik Psikofarmakoloji Bulteni2015; 25: 178–182.
30.
KamińskiMŁoniewskiIMiseraA, et al. Heartburn-related internet searches and trends of interest across six western countries: a four-year retrospective analysis using Google ads keyword planner. Int J Environ Res Public Health2019; 16: 4591.
31.
SilgeJRobinsonD. Text mining with R: a tidy approach. Newton, MA: Oriley, 2017.
32.
GaniIMBahariZ. Islamic banking’s contribution to the Malaysian real economy. ISRA Int J Islam Financ2021; 13: 6–25.
33.
LeeSPIsaMAuzairyNA. The relationships between time deposit rates, real rates, inflation and risk premium: the case of a dual banking system in Malaysia. J Islam Account Busines Res2020; 11: 1033–1053.
34.
BoonTHYeeHSTingHW. Financial literacy and personal financial planning in Klang Valley, Malaysia. Int J Econ Manag2011; 5: 149–168.
35.
OngALeeBK. Personal financial planning in Malaysia: your blueprint to financial success. Singapore: AFPJ, 2001.
Al-AidarosA-HAbdul HadiLNHamdanNA. Islamic wealth planning: the development of instrument. Int J Islam Busines2020; 5: 1–19.
38.
SheLRasiahRTurnerJJ, et al. Psychological beliefs and financial well-being among working adults: the mediating role of financial behaviour. Int J Soc Econ2022; 49: 190–209.
39.
MagliASSabriMFAbdul RahimH, et al. Mediation effect of financial behaviour on financial vulnerability among B40 households. Malay J Consum Family Econ2021; 27: 191–217.
40.
HashimHBCheeALYFernYS, et al. Financial literacy: the influencing factors among youth. Manag Educ Soc Sci2021; 1: 1–10.
41.
YusoffZMEngku AliERAZakariyahH. Islamic financial planning: towards sustaining the financial wellbeing of Muslim families in Malaysia post Covid-19. Turkish J Islamic Econ2021; 8: 355–376.
42.
WeiCYMohammad IsmailNHMd YunusZB, et al. Parental saving: does SSPN matter to my children’s education?J Global Bus Social Entrepreneur2018; 4: 16–29.
43.
EdehFOAryaniDNSubramaniamTAP, et al. Impact of COVID-19 pandemic on consumer behavior towards the intention to use e-wallet in Malaysia. Int J Account Finance Asia Pasific2021; 4: 42–59.
44.
KarimMWHaqueAUlfyMA, et al. Factors influencing the use of E-wallet as a payment method among Malaysian young adults. J Int Bus Manag2020; 3: 1–12.
45.
HussainAMkpojioguEOCMohmad KamalF, et al. An instrumental assessment of touch’n Go eWallet mobile app. Int J Interact Mobile Tech2021; 15: 4–17.
46.
Abd RahmanNAZamriMSN. Faktor yang mempengaruhi pensyarah melabur dalam Amanah Saham Bumiputera (ASB). J Busines Innov2020; 5: 56–62.
47.
SitirisiMMahmudiiMWZakariaMS, et al. Exploring the fatwa methodology of committee of the national council for Islamic affairs: case of ASB trust fund. J Fatwa Manag Res2020; 19: 1–17.
48.
VaghefiNKariFTalibMA. Poverty and income replacement profile among EPF retiree in Malaysia. Soc Indic Res2017; 132: 1065–1078.
49.
IsamailMZYa’acobFFSulaimanZ, et al. Implications of moratorium on Islamic financial customers in Malaysia. Int J Asian Soc Sci2021; 11: 259–269.
YaoJ. Automated sentiment analysis of text data with NLTK. J Phys Conf Ser2019; 1187: 052020.
52.
IgnatowGMihalceaR. An introduction to text mining: research design, data collection, and analysis. New York: Sage, 2018.
53.
RosidMAFitraniASAstutikIRI, et al. Improving text preprocessing for student complaint document classification using sastrawi. IOP Conf Ser Mater Sci Eng2020; 874: 012017.
54.
Al-AnaziSAlmahmoudHAl-TuraikiI. Finding similar documents using different clustering techniques. Procedia Comput Sci2016; 82: 28–34.
55.
ŽižkaJDařenaFSvobodaA. Text mining with machine learning. Boca Raton, FL: CRC Press, 2019.
YouJShaikNChenH. Data mining on COVID-19 vaccines: side effects. Proc Assoc Inform Sci Tech2021; 58: 869–871.
58.
NickersonRCVarshneyUMuntermannJ. A method for taxonomy development and its application in information systems. Eur J Inform Syst2013; 22: 336–359.
59.
DiMaggioPNagMBleiD. Exploiting affinities between topic modeling and the sociological perspective on culture: application to newspaper coverage of U.S. Government arts funding. Poetics2013; 41: 570–606.
60.
RobinsonSD. Temporal topic modeling applied to aviation safety reports: a subject matter expert review. Saf Sci2019; 116: 275–286.
61.
YusoffMSB. ABC of content validation and content validity index calculation. Educ Med J2019; 11: 49–54.
Md JelasIAhmadAB. Profitability of investment in government-sponsored unit trust funds (ASB unit trust fund) through term loan facility: a backtesting approach. Proceedings book of ICEFMO, 2013, Malaysia handbook on the economic, finance and management outlooks, Conscientia Beam, 2013, pp. 504–513.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
