Introduction
This paper is about if there is a relationship between General Data Protection Regulation (GDPR) and Personal Data in terms of web search in specific periods. To do so, Google Trends Statistics have been used. The comparisons were made by using world wide web searches for the topics of GPDR and Personal Data. Worldwide web searches were chosen since one can go to one country at a time in Google Trends. Meaning, one can only look for one country for her/his research in each data collection. The Law & Government was selected as a category for one independent variable. Personal Data from GDPR’s website[1] has been selected as a key issue. The beginning of this paper is about the definitions made by this law for GPDR’s Subject-matter and objectives and Personal Data.
General Data Protection Regulation (GPDR)
This law has been enacted by the EU on 14 April 2016. What is GDPR? Article 1 of GDPR, the EU has defined GPDR’s Subject-matter and objectives by saying that;
“This Regulation lays down rules relating to the protection of natural persons with regard to the processing of personal data and rules relating to the free movement of personal data.
This Regulation protects fundamental rights and freedoms of natural persons and in particular their right to the protection of personal data.
The free movement of personal data within the Union shall be neither restricted nor prohibited for reasons connected with the protection of natural persons with regard to the processing of personal data.[2]”
On GDPR’s website, it says “The European Data Protection Regulation is applicable as of May 25th, 2018 in all member states to harmonize data privacy laws across Europe.[3]” Because of this statement given above, my comparisons between GDPR and Personal Data will start on 25 May 2018.
Personal Data
Personal Data has been defined by the GPDR by saying that;
“‘personal data’ means any information relating to an identified or identifiable natural person (‘data subject’); an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person;[4]”
Evaluation
Given both statements for GPDR and Personal Data, one can understand GDPR acknowledges fundamental rights and freedoms of natural persons, and also this law acknowledges the freedom of personal data. One can evaluate from this sentence GDPR does not restrict the movement of personal data, it allows the movement of personal data by protecting natural persons’ rights. Since topics of data protection, personal data, and the laws related to these two terms are unfamiliar to many people, it would be interesting to analyze the public’s searches on Google Trends. One can find a powerful correlation if her/his researches contain fresh topics. Also, shedding light on untouched fields is always expected from researchers.
Limitations of the Study and Ethical Issues
The many variables might fit this study's rhetoric. They might have been applied in this study too. However, more variables mean more time. This example is the very reason why some variables have not been added to this study. One has to be careful while doing any kind of research. Therefore this project is not an evaluation of any methods that have been made. The criteria in the methods are examined based on the selected variables. This study only includes suggestions and interpretations of the given methods’ applications. In addition to that argument, Lawrence Neuman (2014) stated that “statistics may be inappropriate for your research question”. Because every research has been designed to find some specific issues. The scholars are collecting their data to find what they needed to find. This is another reason why the stats that have been shown in this study do not claim any academic research. Data has been gathered from Google Search Trends. So, people who search the words “GDPR” and “Personal Data” websites might not want to share their data without any consent. Even though Google Searching Trends publicly opens its dataset, this situation cannot be used as an excuse. Meaning, the Consent Letter (Bryman, 2012, pp. 129-155) and the Ethical Approval (Gelling, 2016) from the committee must be taken if this study will be academic research.
The Methods
Tests for one independent variable,
The simple linear regression has been used by comparing GDPR and Personal Data searches (Mehra, 2003; Seltman, 2012; Lane et al., 2017). To do so, Excel’s Data Analysis tool has been used. GPDR was the independent variable in this research, and Personal Data was the dependent variable. Because GDPR affects Personal Data on many occasions, such as protecting the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person[5]. Before GPDR, Personal Data existed, but based on protecting personal data will not be the same. The main hypothesis was;
H0: There is not a relationship between searching trends for GDPR and searching trends for Personal Data.
H1: There is a relationship between searching trends for GDPR and searching trends for Personal Data.
The second three month-period has been selected[6]. Also, other statistical results have been added to this research. The major event is GDPR. The results were given below;
Findings and Hypotheses Testing
29 September 2018-1 July 2018
R-square is 0.65 and the correlation value is 0.81 (Zou, Tuncali & Silverman, 2003). One can say there is a positive correlation between GPDR and Personal Data searching trends. Their relationship is powerful.
The searching trends orderly close to the true regression line. Meaning, they are not perfectly close.
The gap between the two searching trends means is high. However, interestingly, this result is going to affect our testing results positively.
Hypothesis Testing
H0: There is not a relationship between searching trends for GDPR and searching trends for Personal Data.
H1: There is a relationship between searching trends for GDPR and searching trends for Personal Data.
According to our Simple Linear Regression Test, p-value < α. From that result, we reject the null hypothesis, and with a 95% confidence level, we can say there is a relationship between GPDR and Personal Data in terms of web searches (Hosmer & Lemeshow, 1992). One might say searching trends for GPDR has affected searching trends for Personal Data.
In addition to testing results, Adjusted R Square is close to R Square value. Meaning, Adjusted R Square validates the R-Square value. There would be an issue if they are not close to each other.
Another graphic is about residuals. In this graphic important detail is that residuals are not far away from zero. They are not close to zero either. However, they stay at a somewhat expected level.
Discussion
Overall, it can be stated that there is a relationship between searching trends for GDPR and searching trends for different periods. But saying there is a relationship that does not show any researcher an entire picture of GDPR or Personal Data conversations. For future researches, adding interviews to this type of researches could shed more light on knowledge about Data Protection Laws, their definitions, and awareness of data protection processes. Another suggestion might be changing the search trends from worldwide to more applicable ones. The other suggestion might be, the researchers could add machine learning techniques to prove their hypotheses. Also, data can be normalized to reach more accurate results (Dodge & Commenges, 2006). Time Series Analysis methods can be applied (Woodward, Gray & Elliott, 2017).
Conclusion
GDPR has been enacted on 14 April 2016. From that date, the movement of personal data has been regulated. Controllers who process personal data need to follow GDPR’s regulations. But as a natural person, one might not know what she/he needs to do. Also, not everyone has the privilege to go to lawyers. So, a simple Google search could be an expected outcome for most people. Given that explanation, the next question wanted to be analyzed if there is a relationship between GDPR and Personal Data topics on web searches. This study proves that GDPR has affected Personal Data searches on Google Trends. The purpose of this project is to shed a light on data protection laws' affection for our lives. As data subjects[7], we should learn our fundamental rights.
Bibliography
Bryman, A. (2012). Social research methods. Oxford: Oxford University Press.
Dodge, Y., & Commenges, D. (Eds.). (2006). The Oxford dictionary of statistical terms. Oxford University Press on Demand.
Gelling, L. H. (2016). Applying for ethical approval for research: the main issues. Nursing Standard, 30(20), 40-44.
Hosmer, D. W., & Lemeshow, S. (1992). Confidence interval estimation of interaction. Epidemiology, 452-456.
Lane, D. M., Scott, D., Hebl, M., Guerra, R., Osherson, D., & Zimmer, H. (2017). Introduction to statistics. Houston: Rice University.
Lawrence Neuman, W. (2014). Social research methods: qualitative and quantitative approaches. Pearson.
Mehra, A. (2003). Statistical sampling and regression: simple linear regression. PreMBA analytical methods. Columbia Business School and Columbia University.
Seltman, H. J. (2012). Experimental design and analysis.
Woodward, W. A., Gray, H. L., & Elliott, A. C. (2017). Applied time series analysis with R. CRC press.
Zou, K. H., Tuncali, K., & Silverman, S. G. (2003). Correlation and simple linear regression. Radiology, 227(3), 617-628.
[1] https://gdpr-info.eu/issues/ Key Issues section. There are 12 key issues according to GPDR. [2] https://gdpr-info.eu/art-1-gdpr/ [3] https://gdpr-info.eu/ [4] https://gdpr-info.eu/art-4-gdpr/ Article 4 Paragraph 1 [5] https://gdpr-info.eu/art-4-gdpr/ Article 4 Paragraph 1 [6] There is no scientific back story here in this three-month-long research. Other suitable dates have been visited and this timeline has been selected. [7] https://gdpr-info.eu/art-4-gdpr/ Article 4 Paragraph 1: ‘personal data’ means any information relating to an identified or identifiable natural person (‘data subject’); an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person;