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Dating For Success: The Best Way, Statistically, To Find The One
When thinking of creating the visualization, I wanted to develop a report that would not only make the audience interested in the topic, but also lead them to develop their own conclusions. Although there were many statistical datasets out there that I could use, I ultimately decided to go with a topic that was more personal to the viewer, and this was the topic of dating. I was interested in portraying to my viewers which method of dating was the most successful in finding a partner. Ultimately, I narrowed this down between the comparison of online vs. in-person dating, especially since technology has reached a peak and many of the people I have talked to still crave an in-person connection while simultaneously being on dating apps. This was an interesting area to explore, so I decided to pursue this comparison based on demographics such as gender, sexual orientation, and ethnicity.
As for data, this was slightly more tricky because there were no comprehensive datasets that could be exported to a CSV and extracted in Tableau or another visualization software. However, there was abundant data from research organizations such as Pew Research which consisted of surveys and other research studies asking questions to a large group of individuals and garnering responses. I decided to use this statistical data to aid in my visualizations, and I created my own dataset/spreadsheet based on the survey responses and other data that I discovered in the research studies.
Based on this data and the topic, I completed Part 1, and identified what I wanted to create as my project along with sketches outlining the user story and potential visualizations I would use in the project.
I identified the audience of my presentation in Part 2 as my classmates, since I would be presenting to them. My subset of classmates represents a larger set of adults living in the U.S. (either temporarily or permanently) ages 18-30. Although I initially defined the audience in Part 2 as just my classmates, I am amending this for Part 3 and identifying the audience as 18-29 year old adults living in the United States of America. Despite the topic being the most helpful for those who are single, I still think that it is interesting to include people who are not single as part of my audience because they may be interested in the statistics, compare how they met their partner to my data, and even offer this advice to their single friends. As someone in a relationship, I found this data very interesting so I believed that narrowing down the audience to just single adults was not the right move. This audience was represented in a variety of ways in Part 2, with the most prevalent being through a user study and personas.
I first created the personas to represent two different audience members who may be interested in my story. I made two personas with completely different demographics relating to age, gender, sexual orientation, and background. This gave me a diverse perspective of the thoughts of potential individuals who may view my presentation. Using the personas, I was able to pinpoint that I wanted my presentation to be somehow personalized; doing this with many different audience members of different backgrounds was a challenge, so I came up with an idea to create a demographic table at the end of the presentation to show the audience that for their specific demographics, there is a specific recommended dating method.
The user study was also a great way to get feedback on the initial ideas I had developed for the presentation. I selected four different participants who matched different demographics and backgrounds, showed them the current layout of my draft presentation from Part 1, and asked them follow up questions about their thoughts. Through this method, I found out that all participants agreed that they wanted more complexity of graphs and specific graphs related to different demographics. They also wanted a deeper dive into demographic statistics, which led me to implement the table in the end of the report so that all members of the audience could relate to the chart and recommendations.
Based on this feedback, I implemented the following changes (as mentioned in Part 2) to my final design:
Final Sources Used for Data: https://www.pewresearch.org/short-reads/2023/02/02/key-findings-about-online-dating-in-the-u-s/
https://ssrs.com/insights/the-public-and-online-dating-in-2024/
https://www.pnas.org/doi/10.1073/pnas.1908630116
https://thrivingcenterofpsych.com/blog/dating-in-2023-here-is-where-most-singles-are-living-in-the-us/
https://www.pewresearch.org/short-reads/2023/06/26/about-half-of-lesbian-gay-and-bisexual-adults-have-used-online-dating/
https://phys.org/news/2024-10-dating-apps-sites-diverse-couples.html
There were many changes made in Part 2 in order to improve and create the visualization in Part 3. The first difference was in design; I moved my visualization from sketches to the Shorthand platform, which provided for a professional design. I also edited the color scheme to be broader, but not as broad as I wrote in Part 2. Instead of creating a color scheme with a variety of different pinks, oranges, and reds, I decided to create my color scheme as hot pink, light purple, white, and black. This allowed for a greater diversity in colors but kept the colors cohesive in my presentation. For the final presentation, I received a complement from one of my classmates on the consistent color scheme, so it was great that I could confirm that this color scheme worked well.
I also changed the graph types and added more data via visualizations created in Tableau. I included bar graphs including a stacked bar graph, a circle graph, and a line graph. I also added labels on the graphs to make sure I was pointing to important parts of the graph. The other change I made to the design was that I included bolded statistics in between each graph. This was a design choice that I thought would be easier to present to my audience, since they would be able to see a large statistic, such as what percentage of adults were currently using dating apps, and remember that number/insight. I used my color scheme in the graphs and to write the statistics on-screen so that attention would be drawn to the text/graphs.
For the final visualization, I made sure to include headers, background pictures, and citations for all pictures/statistics/graphs. I also clearly defined a success metric in the data I was using, since this was something pointed out in the in-class reviews of the project drafts. The success metric was defined early-on in the presentation as being getting into a couple. I defined assumptions related to this metric and the studies that I used as well. I also included a clear call to action at the end, with a table identifying based on different demographics, what the recommended dating methods are and their levels of success. This table personalized the call to action to every audience member, who could locate their own demographics in the table and see what their best chance at dating is.
Overall, I truly enjoyed creating this project and visualization. I learned a lot about online and in-person dating, how different demographics have different success levels, and the current trends of young adults in the United States. I learned great takeaways from this and developed a lot of design and visualization experience!