Abstract
This paper aims to propose an effective method to locate valuable reviews of mobile phones for older adults. After collecting the online reviews of mobile phones for older adults from JD mall, we propose a three-step framework. Firstly, Topic Modeling models and linguistic inquiry and word count (LIWC) methods are employed to extract latent topics. Secondly, regression models are used to examine the effect of variables obtained from the first step on the popularity (number of replies) and usefulness (number of helpful counts). Thirdly, seven machine learning models are adopted to predict the popularity and usefulness of online reviews. The results indicate that although older adults are more interested in the exterior, sound, money, and communication functions of mobile phones, they still care about the touch feel, work, and leisure functions. In addition, Random Forest performs the best in predicting the popularity and usefulness of online reviews. The findings can help e-commerce platforms and merchants identify the needs of the targeted consumers, predict which reviews will get more attention, and provide some early responses to some questions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Akca, M. Sayili, K.: Theory and practice: Esengun challenge of rural people to reduce digital divide in the globalized world. Gov. Inf. Q. 24, 404–413 (2007)
Ball, C., Francis, J., Huang, K.T., Kadylak, T., Cotten, S.R., Rikard, R.V.: The physical-digital divide: exploring the social gap between digital natives and physical natives. J. Appl. Gerontol. 38(8), 1167–1184 (2019)
Billon, M., Lopez, F.L., Marco, R.: Differences in digitalization levels: a multivariate analysis studying the global digital divide. Rev. World Econ. 146, 39–73 (2020)
Cao, H.H.: Online review manipulation by asymmetrical firms: is a firm’s manipulation of online reviews always detrimental to its competitor? Inf. Manag. 57(6), 103244 (2020)
Chang, S.I., Yen, D.C., Chang, I.C.: Study of the digital divide evaluation model for government agencies - a Taiwanese local government’s perspective. Inf. Syst. Front. 14, 693–709 (2012)
Choi, J., Oh, S., Yoon, J., Lee, J.M., Coh, B.Y.: Identification of time-evolving product opportunities via social media mining. Technol. Forecast. Soc. Chang. 156, 120045 (2020)
Cruz-Jesus, F., Oliveira, T., Bacao, F., Irani, Z.: Assessing the pattern between economic and digital development of countries. Inf. Syst. Front. 19(4), 835–854 (2016). https://doi.org/10.1007/s10796-016-9634-1
Duplaga, M.: Digital divide among people with disabilities: analysis of data from a nationwide study for determinants of internet use and activities performed online. PLoS ONE 12(6), e0179825–e0179825 (2017)
Estacio, E.V., Whittle, R., Protheroe, J.: The digital divide: examining socio-demographic factors associated with health literacy, access and use of internet to seek health information. J. Health Psychol. 24(12), 1668–1675 (2019)
Fuchs, C.: The role of income inequality in a multivariate cross-national analysis of the digital divide. Soc. Sci. Comput. Rev. 27(1), 41–58 (2009)
Ghasemaghaei, M., Hassanein, K., Benbasat, I.: Assessing the design choices for online recommendation agents for older adults: older does not always mean simpler information technology. MIS Q. 43(1), 329–346 (2019)
Hall, A.K., Bernhardt, J.M., Dodd, V., Vollrath, M.W.: The digital health divide: evaluating online health information access and use among older adults. Health Educ. Behav. 42(2), 202–209 (2015)
Huang, S.-C., Cox, J.L.: Establishing a social entrepreneurial system to bridge the digital divide for the poor: a case study for Taiwan. Univ. Access Inf. Soc. 15(2), 219–236 (2014). https://doi.org/10.1007/s10209-014-0379-7
Jara, I., et al.: Understanding factors related to Chilean students’ digital skills: a mixed methods analysis. Comput. Educ. 88, 387–398 (2015)
Jiang, S., Hong, Y.A., Liu, P.L.: Trends of online patient-provider communication among cancer survivors from 2008 to 2017: a digital divide perspective. J. Cancer Surviv. 13(2), 197–204 (2019). https://doi.org/10.1007/s11764-019-00742-4
Kiss, H., Fitzpatrick, K.M., Piko, B.F.: The digital divide: risk and protective factors and the differences in problematic use of digital devices among Hungarian youth. Child Youth Serv. Rev. 108, 104612 (2020)
Li, M.X., Huang, P.: Assessing the product review helpfulness: affective-cognitive evaluation and the moderating effect of feedback mechanism. Inf. Manag. 57, 103359 (2020)
Loo, B.P.Y., Ngan, Y.L.: Develo** mobile telecommunications to narrow digital divide in develo** countries? Some lessons from China. Telecommun Policy 36, 888–900 (2012)
Loo, B.P.Y.: The e-society. Nova Science, New York (2012)
Manzuch, Z., Maceviciute, E.: Getting ready to reduce the digital divide: scenarios of Lithuanian public libraries. J. Am. Soc. Inf. Sci. 71, 1205–1217 (2020)
Mudambi, S.M., Schuff, D.: What makes a helpful online review? a study of customer reviews on Amazon.com. MIS Q. 34(1), 185 (2010)
Mumporeze, N., Prieler, M.: Gender digital divide in Rwanda: a qualitative analysis of socioeconomic factors. Telematics Inform. 34, 1285–1293 (2017)
Neves, B.B., Waycott, J., Malta, S.: Old and afraid of new communication technologies? reconceptualising and contesting the ‘age-based digital divide.’ J. Sociol. 54(2), 236–248 (2018)
Niehaves, B., Plattfaut, R.: Internet adoption by the elderly: employing IS technology acceptance theories for understanding the age-related digital divide. Euro. J. Inf. Syst. 23, 708–726 (2014)
Olson, K.E., O’Brien, M.A., Rogers, W.A., Charness, N.: Diffusion of technology: frequency of use for younger and older adults. Ageing Int. 36, 123–145 (2011)
Park, S.R., Choi, D.Y., Hong, P.: Club convergence and factors of digital divide across countries. Technol. Forecast. Soc. Chang. 96, 92–100 (2015)
Petrovic, M., Bojkovic, N., Anic, I., Petrovic, D.: Benchmarking the digital divide using a multi-level outranking framework: evidence from EBRD countries of operation. Gov. Inf. Q. 29, 597–607 (2012)
Potnis, D.: Inequalities creating economic barriers to owning mobile phones in India: Factors responsible for the gender digital divide. Inf. Dev. 32(5), 1332–1342 (2016)
Reddick, C.G., Enriquez, R., Harris, R.J., Sharma, B.: Determinants of broadband access and affordability: an analysis of a community survey on the digital divide. Cities 106, 102904 (2020)
Sachdeva, N., Tuikka, A.M., Kimppa, K.K., Suomi, R.: Digital disability divide in information society. J. Inf. Commun. Ethics Soc. 13(3/4), 283–298 (2015)
Song, Z.Y., Wang, C., Bergmann, L.: China’s prefectural digital divide: spatial analysis and multivariate determinants of ICT diffusion. Int. J. Inf. Manage. 52, 102072 (2020)
Szeles, M.R.: New insights from a multilevel approach to the regional digital divide in the European Union. Telecommun. Policy 42, 452–463 (2018)
Teso, E., Olmedilla, M., Martinez-Torres, M.R., Toral, S.L.: Application of text mining techniques to the analysis of discourse in eWOM communications from a gender perspective. Technol. Forecast. Soc. Chang. 129, 131–142 (2018)
Tirunillai, S., Tellis, G.J.: Mining marketing meaning from online chatter: strategic brand analysis of big data using latent dirichlet allocation. J. Mark. Res. 51(4), 463–479 (2014)
Townsend, L., Sathiaseelan, A., Gorry, F., Wallace, C.: Enhanced broadband access as a solution to the social and economic problems of the rural digital divide. Local Econ. 28(6), 580–595 (2013)
Wang, J.N., Du, J.Z., Chiu, Y.L.: Can online user reviews be more helpful? evaluating and improving ranking approaches. Inf. Manag. 57, 103281 (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Shou, M., Bao, X., Yu, J. (2022). Predictions on Usefulness and Popularity of Online Reviews: Evidence from Mobile Phones for Older Adults. In: Kurosu, M., et al. HCI International 2022 - Late Breaking Papers. Design, User Experience and Interaction. HCII 2022. Lecture Notes in Computer Science, vol 13516. Springer, Cham. https://doi.org/10.1007/978-3-031-17615-9_33
Download citation
DOI: https://doi.org/10.1007/978-3-031-17615-9_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-17614-2
Online ISBN: 978-3-031-17615-9
eBook Packages: Computer ScienceComputer Science (R0)