NM2207 Final Project
About
This project aims to find stories in data through visualization via shiny, ggplot2, echarts4r and other functions with Rstudio.
Background:
Analysis
Top Hate Words
From another data set4, I decided to create a Word Cloud with Shiny to find out more about the words that are most used when people are posting comments that are considered as being hateful. The Word Cloud highlights the predominant themes associated with hateful comments, such as those related to gender, race, and religion. With more using the social media, it is important that users are more mindful of what they post online to contribute to a healthy digital environment that promotes understanding, empathy, and constructive dialoague.
From the data set, there are way too many unique words used, and it is impossible to fit all of them in the word cloud. Hence I included a reactive slider to limit the number of words to be included in the word cloud. I also specifically removed some of the most used words such as “that”, “like”, etc… that are very obviously words that are hateful.
Conclusion
In conclusion, the impact of social media on its users is undeniably complex, encompassing both positive and negative aspects. While the negative effects are particularly pronounced for children, given their heightened susceptibility to external influences, it is crucial to recognize that social media has also introduced numerous benefits into our lives.
However, the narrative takes a distinct turn when considering children, who may lack the cognitive maturity to navigate the online world responsibly. In this context, social media companies bear a significant responsibility to carefully curate content and consider the potential impact on young, impressionable minds. Striking a balance between fostering a positive online environment and protecting the well-being of children requires a collective effort from parents, educators, and the platforms themselves.
As we navigate the intricate landscape of social media, there is a need for conscientious use, regardless of age. Education on digital literacy, responsible online behavior, and age-appropriate content consumption should be prioritized. By fostering a culture of mindfulness and responsible digital citizenship, we can harness the positive aspects of social media while mitigating its potential adverse effects, particularly for the younger members of our society.
References
- Lau, D. (2023, July 24). The big read: Teenagers hooked on social media - what’s the cost to their mental health? CNA. https://www.channelnewsasia.com/singapore/big-read-teenagers-social-media-addiction-cost-mental-health-3647121
- Ahmed, S., & Syeda, M. N. (2023, July). Social Media and Mental Health. https://www.kaggle.com/datasets/souvikahmed071/social-media-and-mental-health/data.
- Dean, B. (2023, November 15). How many people use Social Media in 2023? (65+ statistics). Backlinko. https://backlinko.com/social-media-users#social-media-usage-stats
- Das, S. (2022, November 1). Social media hate comments. Kaggle. https://www.kaggle.com/datasets/subhajeetdas/hate-comment
- Robinson, L., & Smith, M. (2023, March 29). Social Media and Mental Health. HelpGuide.org. https://www.helpguide.org/articles/mental-health/social-media-and-mental-health.htm#:~:text=using%20social%20media.-,Modifying%20social%20media%20use%20to%20improve%20mental%20health%20step%201,%2C%20sleep%20problems%2C%20and%20FOMO.
- Baptist Health. (2020, November 6). How social media affects attention span. https://www.baptisthealth.com/blog/family-health/how-social-media-affects-attention-span#:~:text=Not%20only%20are%20attention%20spans,decreased%20attention%20on%20each%20task.
- Nuno, S. (2023, February 14). How does social media affect sleep? (2023). Mattress Clarity. https://www.mattressclarity.com/sleep-resources/social-media-affects-sleep/#:~:text=Social%20Media%20and%20Insomnia,understanding%20of%20when%20bedtime%20is.
- Cramer, S., & Inkster, B. (2017, May). #StatusOfMind Social media and young people’s mental health and wellbeing. https://www.rsph.org.uk/our-work/campaigns/status-of-mind.html
- MacRae, D. (2022, June 22). 89% of people feel social media negatively affects their mental health. Marketing Tech News. https://www.marketingtechnews.net/news/2022/jun/22/89-of-people-feel-social-media-negatively-affects-their-mental-health/
- Mir, E., & Sun, A. (2023, July 20). Social Media and adolescents’ and Young Adults’ mental health. National Center for Health Research. https://www.center4research.org/social-media-affects-mental-health/
- Newport Academy. (2023, August 3). The theory of social comparison and Mental Health. https://www.newportacademy.com/resources/empowering-teens/theory-of-social-comparison/
Social Media Usage
We will first start off with analyzing the usage of social media among our respondents from the dataset.
Before we start, this is how I mutated the dataset to better observe trends that are more applicable to focus of the project. From the data set, I created a new column, age_group to separate the respondents into different age groups as seen from the drop down menu based on the respective age range the respondents fall into to further analyse the impact of one’s age. While those who are under 16 years old are usually considered as a “Child”, I have expanded the age range to below “25” accordingly since it is the age range where they are more susceptible to being negatively affected by social media as mentioned earlier1
From the donut chart below, this data set is a good one to work with to investigate the impacts of social media on children as majority of our respondents do fall under the “child” category.
Starting off with our Pie Chart in the first tab, it is evident that most of the respondents from our data set uses social media.
To further breakdown on our demographics, the Bar Chart in our second tab categorises our respondents and their social media usage tendency according to their ages. From the bars, a similar conclusion can be drawn: most of our respondents are in their 20s, and they do use social media.
Our data set also has a column consisting of the different social media platforms that are used by the respondents. This bubble chart illustrates the various platforms used, alongside their popularity. It can be observed that among the respondents, the top 3 most commonly used platforms are Facebook, Instagram and Youtube.
Average time spent on social media daily
Next, we investigate the average time spent on social media daily by our respondents. The interactive stacked bargraph indicates that the largest group of respondents spends more than 5 hours of their time on social media daily on average. To further breakdown on this bar chart, we remove all age groups other than “Child”. A general increasing trend in the usage duration of social media is observed, and the majority of them spends > 5h on social media. This is an extremely concerning phenomenon as a study conducted by the University of Pennsylvania in 2018 revealed that daily social media usage that exceeds 30 minutes led to heightened anxiety, depression, feelings of loneliness, sleep disturbances, and the fear of missing out (FOMO).5
notes:
Clicking on either of the legend at the top will remove the plot respectively