Balearic Islands University (SPAIN)
About this paper:
Appears in: INTED2022 Proceedings
Publication year: 2022
Page: 2294 (abstract only)
ISBN: 978-84-09-37758-9
ISSN: 2340-1079
doi: 10.21125/inted.2022.0665
Conference name: 16th International Technology, Education and Development Conference
Dates: 7-8 March, 2022
Location: Online Conference
The analysis of data derived from Internet searches is a growing research method used in various fields. For example, it has been applied in medium-term forecasting studies such as the analysis of: unemployment trends, consumer goods preferences and in studies of prediction of electoral results. Also, it has been used in nowcast studies to allow obtaining relevant information much earlier than through traditional data collection techniques. Likewise, it has been used in studies that detect problems related to health, the environment and well-being in general. Finally, it has been used to measure complex processes where traditional data show known deficits, for example, for international migration studies.

In line with the conclusions of Ginsberg et al. (2009) this contribution argues that web search data can be used to track various social phenomena and provide more timely and up-to-date information than data emanating from traditional methodological approaches. The Internet has become a primary source of information for tracking and monitoring online activities. In this context, data related to Internet searches is especially important and valuable since it reflects the “needs, desires, interests and concerns” of people (Ettredge et al., 2005, p. 87) and has an evident capacity to improve knowledge of human behavior. An example of this is the potential that this methodology has for the study of dishonest behavior among students, a field of analysis with growing interest and a documentary corpus at an international level. Knowing what students are looking for and how they seek information, resources and strategies to carry out dishonest behaviors in the framework of their studies (plagiarism, cheating on exams, buying academic papers, etc.) has great potential to complement the evidence derived from studies existing in this field derived from methodological research procedures that we could classify as traditional (surveys, questionnaires, interviews, discussion groups, etc.) of which, due to the very nature of the phenomenon under analysis, it has been criticized that they suffer from significant biases. related to the social desirability of the study participants. The use of information search metrics on the internet can partly solve this problem and improve existing knowledge on the subject. In this presentation, some examples and potential developments and applications of this type of analysis will be presented.

This paper is part of the project IAPOST grant RTI2018-098314-B-I00 funded by MCIN/AEI/ 10.13039/501100011033 and by “ERDF A way of making Europe”.

[1] Ettredge, M., Gerdes, J., & Karuga, G. (2005). Using web-based search data to predict macroeconomic statistics. Communications of the ACM, 48(11), 87-92.
[2] Ginsberg, J., Mohebbi, M.H., Patel, R.S., Brammer, L., Smolinski, M.S., & Brilliant, L. (2009). Detecting influenza epidemics using search engine query data. Nature, 457(7232), 1012–1014.
Academic integrity, research methods, internet search activity.