Internet Usage and Life Quality

By Quinn Vu, Tina Yu, and Mary Mei Longano

Topic Introduction

As technology becomes more integrated into the fabric of society, the world has developed a deep reliance on the internet. The internet plays a pivotal role in the globalization of the economy and the prosperity of developed nations. It serves as a major factor in a nation’s success, such as the exchange of goods and services, spreading of culture, and population growth (Litan & Rivlin, 2001). Along with the unlimited source of knowledge, the internet offers global connectivity that removes the physical boundaries of business and everyday life. Because of its influence on the socioeconomic status of a nation, our team is interested in exploring the relationship between internet usage and the quality of life.

What effect does internet usage have on the quality of life in a nation? In order to narrow down this research question, we define a nation’s quality of life by two factors: GDP and the average life expectancy. GDP per capita is defined as Gross Domestic Product, or the total amount of products and goods produced by a country in a given time, of an average person. It calculates the value of a nation’s business, indicating how successful the economy is in relation to the population. Since a nation’s economy often trickles down into its governance and development, GDP provides a closer picture of the general welfare. In addition to GDP, life expectancy also illustrates the standard of living. In a recent study comparing countries’ average life span to income, the life expectancy average can be a result of numerous factors like healthcare, education, and housing (Freeman et al., 2020). It can roughly indicate how comfortable and secure the average citizen is. With the quality of life defined by these two factors, we intend to determine the internet’s effect through data visualizations.

Data introduction

We used Tableau to create the visualizations and retrieved our dataset from the World Development Indicators. While our previous definition of business was expressed in qualitative data, GDP is an established form of quantitative measurement. It is defined by the market value per capita, expressed on the x-axis in $20,000 intervals. The average life expectancy is represented with ratio data. Internet usage is measured with quantitative data. It is expressed by the percentage of the country’s population that uses the internet. Depending on the type of data, we utilize different forms of visualizations to best capture the relationship between the two variables.

Internet Usage and Life Expectancy

In order to measure how a country’s life quality is influenced by internet usage, we first looked into the possible correlation between internet usage and life expectancy. As the world is progressing and the internet is becoming a normality in most developed and industrialized nations, it is clear that internet usage can be used as an indication of how developed a nation is. In “Hi speed Internet access impacts quality of life, business”, M. Ray Perryman argues that internet access can directly impact quality of life and business. Demonstrating that there is a high probability that there is a positive correlation between the increase of internet accessibility, and therefore increase of internet usage, and the average life expectancy can be telling of how internet usage can be used as a means of measuring life quality in a country. The visualizations created on Tableau can be used to demonstrate whether or not internet usage and life expectancy can be used as a possible method to show life quality.

By setting aside the parameters necessary in order to create useful visualizations, Tableau will automatically create a graph that they believe the data will be easiest to work with. As shown in Figure 1.1, Tableau knows that in order to see a trend with the measurement of time as the y-axis, line graphs are very useful. After experimenting with other graphs, it is clear that using line graphs will be the best to portray the data; however, we can not use the automatic visualizations that Tableau has created because it is imperfect. The visualization that Tableau created consists of two different x-axis measures on two opposite sides. As explained by Jeffrey Heer and Ben Shneiderman in Interactive Dynamics for Visual Analysis, filtering your data is important as analysts often will want to focus on different data subsets and use guides to create a story (pp. 4). The automatic Tableau visualization does not have any tools that would allow for users to filter or explore the data.

Figure 1.1: Automatic Tableau visualization

In order to eliminate the confusion that the automatic Tableau visualization creates, we created a new visualization that incorporates what we felt that the automatic Tableau visualization does well as well as implement some changes that could help viewers navigate the visualization in the most practical way (Figure 1.2). Instead of having two lines to indicate internet usage and life expectancy, we chose to have the line represent the change over time of the average internet usage as a population. In order to represent the change of time of the average life expectancy, we decided to use labeling and red color coding. The red color palette goes from a light pink shade indicating the lower end of the range to a deep red shade indicating the higher end of the range. We also added in a trend line so that we can make use of Tableau’s trend line model (Figure 1.3). Viewers will be able to filter the data by changing the region as they wish on the right side making this interactive.

Figure 1.2: Line graph with trend line visualization

Figure 1.3: Trend line model

Internet Usage and GDP Per Capita

The second criteria we are using to test our thesis is by looking into the correlation between internet usage and GDP per capita of the countries. GDP is calculated by taking the GDP and dividing it by the population of the country. Because of this formula, GDP per capita demonstrates the economic health and life quality of a country by showing whether or not its production equates to its population, and also what we believe to dictate the country’s living standards. A country with a low GDP per capita may be struggling to provide adequately for their population, whereas a country with a high GDP per suffices and exceeds in supplying for their people. There is no baseline for what is considered a low versus a high GDP per capita, but there are big discrepancies between countries around the world. An estimation by Blah states that Luxembourg has the highest GDP per capita, at $131,782, and Burundi the lowest at $265 in 2021 (cite).

Our previous data visualization research shows that there was indeed a positive connection between internet usage and ease of business (Longano et al., 2021). However, business practices bare little representation of a country’s living quality. Therefore, using a dataset that strays away from mere economic value is important to answer our research question regarding internet usage and life quality.
We placed the two datasets into the row and column bar accordingly, which Tableau then automated into an area/line graph (Figure 2.1). Internet usage is represented by the Y-axis, and GDP per capita by the X-axis. The numeral information of each topic is encoded by its position on the graph: the higher its position, the greater its internet usage, and the further to the right, the larger its GDP per capita. However, even though lines are effective in showing a general trend, the large amount of data we are working with makes this goal more difficult. Inspired by this struggle, we shifted the chart to a scatter plot with a trend line automated by Tableau instead. We found this method more (and the most out of all iterations) effective due to its clarity in pointing out a trend, which is ultimately our main goal. In this final iteration of our visualization, each dot represents each country, with the same encoding tactic as the initial design. Our final visualization is seen in Figure 2.2.

Figure 2.1. First iteration: The area graph plotting internet usage and GDP per capita

Figure 2.2. The scatterplot with a trend line plotting internet usage and GDP per capita

A problem we ran into was the issue of occlusion, which was expected especially when we were working with a dataset this size. Applying Shneiderman’s mantra for data visualization “Overview first, zoom and filter, then details-on-demand”, we decided to make additional information for each country available when a user hovers over a dot (Figure 2.3). Doing so reduces cognitive processing and aligns better with the user’s goal.

Figure 2.3. Details-on-demand as a hover state for each dot

Conclusion

After investigating our research question through data visualizations, we observed a positive relationship between internet usage and the quality of life. When it comes to life expectancy, the line graph shows that the average life span increases over time as internet usage increases with it. As for the GDP, there is a steep increase in internet usage percentage within the first interval of GDP and then it slowly increases the higher the value. While no causation can be assertively determined through these graphs, it is clear that higher internet usage correlates with longer lives and greater economic success. With its influence only growing in magnitude, technology use has become intertwined with the prosperity of a nation. Based on our visualizations, it is safe to say that one can roughly gauge a country’s well-being by the use of the internet.

References

Freeman, T. (2020). Why do some countries do better or worse in life expectancy relative to income? An analysis of Brazil, Ethiopia, and the United States of America. International Journal for Equity in Health. 19(202). https://doi.org/10.1186/s12939-020-01315-z

Heer, J., & Shneiderman, B. (2012). Interactive Dynamics for Visual Analysis. Queue, 10(2), 30–55. https://doi.org/10.1145/2133416.2146416

B. Shneiderman, “The eyes have it: a task by data type taxonomy for information visualizations,” Proceedings 1996 IEEE Symposium on Visual Languages, 1996, pp. 336–343, doi: 10.1109/VL.1996.545307.

Litan, R., & Rivlin, A. (2001, Dec 1). The Economy and the Internet: What Lies Ahead? Brookings. https://www.brookings.edu/research/the-economy-and-the-internet-what-lies-ahead

Perryman, M. R. (2016, May 7). Hi speed Internet access impacts quality of life, business. Midland Reporter-Telegram. https://www.mrt.com/business/article/Hi-speed-Internet-access-impacts-quality-of-life-7419004.php.

List of countries by GDP (nominal) per capita. (2021, May 31). In Wikipedia. https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)_per_capita