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Women in the Digital Age (MKT460 Research Project) Report
- 1. WOMEN IN THE DIGITAL AGE REPORT BY KAITLYN SLACK, ELIZABETH LYBRAND, & MIRA McKEE MKT 460 JOHN DAVIS TTH 12:30-2:00 A Data Analysis Project Regarding UT Females and Their Digital Usage
- 2. OUR EXPLORATION TOPIC What describes a woman in the digital age? What attributes define them, how do they interact with their technology, and what makes them different from other groups of people? EXECUTIVE SUMMARY CONCLUSION OUR ANALYSIS: CROSSTABS OUR ANALYSIS: REGRESSION OUR ANALYSIS: CLUSTERS POSSIBLE EXPLANATIONS AREAS TO EXPLORE CONTENTS:
- 3. A woman in the 21st century can be described by many characteristics. Some may be working, some may stay at home, and some may do both. With technology today, women have endless opportunities to succeed in whatever they want to, but some may take the tool too far. "Women are more at risk in developing addictive behaviors to activities involving elements of social interaction" (Andreassen, 2017). This describes the root of our analysis. Why are women more susceptible to the social media drug? What characteristics make up a woman in this day and age? These are the questions we set out to explore with this data analysis. EXECUTIVE SUMMARY We began by running many crosstabs separating the data by gender, especially targeting 5 questions that we thought would differentiate them. The crosstabs showed us that on average, females are more addicted to social media than males, they get their phones younger, they're more distracted by having their phones out while studying, and they are more productive with their technology than males. A final analytical step we took was to look into the cluster analysis and personas. We found Persona 3 to be the most feminine and compared their data to the data of all the women in our data set. They didn't use their phones much less, just for more productive activities. After all of our analysis, we found that we needed a little more information if we wanted to dive deeper into the data. We thought of a few questions that would help us in our analysis of a typical woman in the digital age. We then ran a stepwise regression to tell us more about the actual top indicative variables for a woman at UT. Our regression came back with 10 variables, but the top 5 were gaming, pretending to be on their phone, feeling guilty about their social media usage, the number of hours a day spent on their phone, and wanting to cut down their social media usage.
- 4. CROSSTABS OUR ANALYSIS Our sample includes both males (48.4%) and females (51.6%) on the UT campus. In order to explore the characteristics of a female in the digital age, we decided to run some crosstabs comparing males and females. First, it is interesting to note that masculinity and femininity are positively correlated with gender; in other words, males are more likely to be masculine, and vice versa. Thus, women in the digital age seem to adhere to a conventional view of gender. Also, more traditionally, females are slightly more extroverted in males. REGRESSION ANALYSIS Then, the crosstabs started to get more interesting. With about 75% of our respondents getting their first mobile smart device before the age of 16, we noticed that more females tended to receive these devices earlier than males. What might the impact of earlier use be on a woman of the digital age? This led us to explore several behavioral characteristics with our crosstabs.
- 5. CROSSTABS OUR ANALYSIS REGRESSION ANALYSIS they felt addicted to social media (108) and had tried to decrease the amount of time they spent on social media (109). Again, the difference in males and females was emphasized by the males’ response. Men strongly do not feel addicted to social media (122) and have not tried to decrease the amount of time they spend on social media (118). First, we looked at productivity between males and females. The index from this crosstabs is inclusive, as both productive and unproductive males and females are within 6 points of the baseline. Next, we looked at how distracted men and women are by social media. At first, it appears that there is not much difference between men (distracted index = 93) and women (106). However, this difference is made more significant by males’ response that they are not distracted by social media (not distracted index = 127, women = 75). There are over 50 points between men and women! The fact that women are more easily distracted by their devices and social media led us to our next crosstabs, looking at addiction and desire to cut down on social media by gender. We saw that females agreed more than males with both of the sentiments— With these indices, we felt like we had a basis of understanding about a woman in the digital age. However, we wanted to know more about what variables were most significantly correlated with gender.
- 6. REGRESSION ANALYSIS OUR ANALYSIS Moving forward with our analysis, we wanted to explore whether or not the 5 original questions that we used to differentiate were actually among the top 5 variables. We ran a stepwise regression analysis with Gender as the Dependent Variable. Through this procedure, we found out the top 10 traits of a woman on UT's campus, in which direction (positively or negatively) the trait implies an individual is likely to be a woman, and how strongly an identifier of a woman the trait is. Below are the top 5 most indicative traits of women at UT. REGRESSION ANALYSIS We were a little surprised to find some of the results of the regression analysis we ran. Gaming was the most indicative trait of UT women, but correlated negatively (meaning if an individual spends less time gaming, they're more likely to be female. We assumed that "pretending to be on your phone to avoid talking to people" was a gender-neutral phenomenon, but apparently it's more common in women! The last three variables in the top 5 did not surprise us at all, however. Through our crosstabs, we saw that women were more addicted and likely to want to cut down, so the regression confirmed our assumption there.
- 7. CLUSTER ANALYSIS OUR ANALYSIS REGRESSION ANALYSIS After we explored differences between females and males, we wanted to look at the personas to see if there were any significant trends. We noticed that Persona 3 was the most female, so we decided to compare and contrast females in general to Persona 3. Most significantly, we noticed that Persona 3 was the most productive persona. This seemed to be a contradiction! How can females be both the second most distracted by their phones and the most productive? We then set out to figure out why this persona was more productive than the average female. We ran a regression to find the variables that most significantly affected productivity among women. Our results showed us that this persona, this group of women, were only using their devices for productive activities (R2 = 18.7%). In other words, this group of women does not use their devices for social media or entertainment. This difference points to why other women are more distracted—they are using their devices for a wider variety of purposes, naturally increasing the probability of distraction.
- 8. POSSIBLE EXPLANATIONS In order to explain the digital characteristics of a woman that we discovered, we came up with a few opinions as to why the women act the way they do. GOT THEIR PHONES YOUNGER: To answer the question as to why women got their phone earlier, we looked at it from a parent's perspective. Young women are more vulnerable in general compared to young men, so they get their phones earlier in order to be able to call their parent at any time. Parents know where their child is at all times through the tracking capabilities of the smartphone. One other explanation we had was the pressure that young women feel as they go through grade school to fit in (e.g., by having a phone like their friends). MORE DISTRACTED WHILE STUDYING: We feel the reason as to why women are more distracted by their phones while studying is because they do not consider social interactions as “distractions.” They feel that texting a friend is a necessary reason to interrupt their studying. Women also turn to social media where men turn to gaming as their distraction of choice while studying. MORE ADDICTED TO SOCIAL MEDIA: The social media gender divide in today’s society is part of the reason women are more addicted to social media than men. They feel more pressure to take care of their image they cater to that on social media platforms. The fact that social media can be accessed at any time of the day also shows why women are more addicted.
- 9. POSSIBLE EXPLANATIONS PRETEND TO BE ON PHONE: When it comes to women pretending to be on their phone to avoid certain people can be explained through safety issues. They tend to feel safer when they do not talk to strangers while walking alone. Women also tend to worry about being on time more than men so this could explain why they'd avoid talking to people while walking to class or to a meeting. MORE GUILTY ABOUT BEING ON SOCIAL MEDIA: The last topic we discussed was why women feel more guilty for being on social media. We believe today’s society creates a standard for young women in that they are the reason social media sites are so popular. People do not always see their social media use as a good thing. The social media platforms such as Instagram and Twitter are considered to be a leisure activity for women, so they feel more guilty about scrolling through their feed. AREAS TO EXPLORE: As we analyzed our data, we realized that if we could do this survey and research project over again, we would've done some things differently. If we had asked a few more questions in our survey we could come up with better answers for our questions. For example, we would've liked to know a person’s description of ‘constructive activities’ because we felt that women could've had a different idea/definition than men. Additionally, distinguishing these categories of smartphone capabilities would help us to have a better description of a woman in this digital age. Finally, we thought women might be more honest if being surveyed by a woman, so that could've been an unintended variable influencing certain answers.
- 10. CONCLUSION Only time and further analysis will tell if our findings contribute to problems faced by women in the digital age, or if they are simply facts of life for females at UT. Through our experiences as women growing up in a fast-paced and ever-changing world, we had an intense curiosity about the defining characteristics of these 'women in the digital age.' We ran many crosstabs between men and women that told us about some of the differences between the genders. Next, we ran a stepwise regression that told us the top 10 most indicative variables of a woman on UT's campus. We then explored the cluster analysis that created four personas and analyzed the difference between Persona 3, a highly female persona, and the rest of the female population. Finally, we gave possible explanations for our findings and even listed some areas to consider exploring and questions to consider asking in the future. Thanks to our newfound understanding of women in the digital age, we have a better gauge of the world, half of UT's campus, and ourselves.