The Evolution of Relationships Pre- and Post-COVID-19
We know that the COVID-19 pandemic can put your health at risk, but can it put your relationships at risk to?
By Aminah Taariq-Sidibe and Maidul Islam
On March 13th, 2020, almost two months after the first reported case in the U.S., former president Donald Trump declared the novel coronavirus a national emergency. This led to a wave of travel bans, social distancing guidelines, and statewide stay-at-home orders. Everything came to a stop, and then radically shifted. Intimate interpersonal relationships were not spared. Coronavirus has for many cause social recession, or the fraying of social bonds. The discussion on how COVID-19 has affected relationships is newly developing. Some articles center on individual stories supported by expert opinion, but what is the opinion based on? Researchers have used methodology such as examining clinical surveys or identifying physical and mental health impacts, but can these capture the exact conflicts that relationships are experiencing? We believe it could be beneficial to identify these conflicts in order to offer direct resources, instead of simply measuring the change in relationships. For this project, we seek to analyze online content about relationships to determine significant topics that are discussed. With this we can begin to form a better understanding about how massive disruptions to social interactions can affect interpersonal relationships in people, and how we can help.
For our project we created two datasets using pulled data from the Reddit.com subcommunity called r/relationship_advice. This subreddit is listed as the 67th largest subreddit in terms of member number, out of almost 140,000 subreddits. This subreddit is dedicated to relationship help, “whether it’s romance, friendship, family, co-workers, or basic human interaction”. We decided to use this subreddit not only for its popularity, but also for its solicitation of advice, which can indicate a conflict. The datasets are broken into the categories ‘score’, ‘title’, ‘author’, ‘selftext’, ‘num_comments’, and ‘subreddit’. The first data set represents pre-COVID-19 (one year before the pandemic was announced) relationships. This data includes 38,034 posts that were uploaded between the dates 03/13/2019–03/13/2020. Below is a word cloud of words with the highest frequency in the pre-COVID-19 dataset.
The second dataset represents post-COVID-19 (one year into the pandemic since it was announced) relationships. This data also includes 38,034 posts that were uploaded between the dates 03/13/2020–03/13/2021. Below is a word cloud of words with the highest frequency in the post-COVID-19 dataset. These word clouds can help us see trends word usage like the reduction in the word ‘work’ or the word ‘sex’ post-COVID-19.
One of the biggest limitations to this analysis is that the topics are only being labeled by two individuals. Different individuals can have different interpretations of what these topics represent. This is also just the perspective of one relationship focused subreddit. Redditors also use popular subreddits like r/relationships, r/dating_advice, r/AskMen, and r/AskWomen to solicit relationship advice. We are also applying some ethical considerations to this analysis. Because we are collecting posts without the consent of each individual poster, we will be paraphrasing the Reddit submissions that are discussed in the article, as well as delete all collected Reddit data after this article is published. There is also a problem of demographics. Since this is only considering the relationship dynamics of Reddit.com users, and the demographics of Reddit.com users are disproportionate, the dynamics can misrepresent the general public. Additionally, according to r/relationship_advice community guidelines, posters are required to disclose the gender and age of individuals discussed in the post, as well as disclose the length of relationship. For this article, we will not be adding these disclosures, or any other identifying information.
The computation method used to retrieve the data was through the Application Programming Interface (API) wrapper named PSAW. We created two API’s that allows us to extract and interact with the data from Reddit.com from two different time periods. The reason we chose this API wrapper is because it’s easier to use than the official Reddit API. We then turned the collected Reddit posts into a Pandas data frame for the analysis. The computation method used for the analysis is Topic Modeling using Little MALLET Wrapper. This method helps us identify the main topics within a collection of texts. The reason we chose to use this was to identify trends in the most frequent topics being discussed and determine the probability distribution of a topic existing in a post. With this wrapper, we isolated the top 15 topics from each dataset that we could examine.
Through this analysis, we were able to identify the top points of conflict Reddit.com users sought advice about. In the post-COVID-19 dataset, there were points of conflict that persisted from the pre-COVID-19 dataset topics. But there were also points of conflict that may be correlated with the new conditions of the pandemic. The topics that were most parallel between the two datasets were ‘Mental and Physical Health Issues’, ‘Sex’, ‘Arguments In Romantic Relationships’, ‘Conflict In Living Situation’ and ‘Break-ups’. These are aspects of relations that already exist but may be changed during the pandemic. ‘Tough Luck With Love’ and ‘To Love Again’ are also similar topics, however the former focuses on losing someone and the latter focuses on getting someone back after losing them. But in the post-COVID-19 topics, there were more topics related to harmful or negative conflict within already established relationships, than there were in the pre-COVID-19 topics. In the pre-COVID-19 dataset, the topics that would indicate harmful conflict in existing relationships are ‘Arguments In Romantic Relationships’ and ‘Conflict In Living Situation’. In the post-COVID-19 dataset, these topics are ‘Arguments In Romantic Relationships’, ‘Relationship Conflicts’, ‘Conflict In Living Situations’, ‘Betrayal and Confusion’, and ‘Relationships Destroying Other Relationships’. We can also see how the context surrounding certain topics change. For example, in the pre-COVID-19 dataset Topic 11 discusses money in terms of bills and careers. But in Topic 1 of the post-COVID-19 dataset, money is discussed in terms of moving or traveling. This may have to do with the uncertainty around travel during the pandemic, but that is only conjecture.
When we zoom into Topic 0, we can also get a sense of how the pandemic has changed relationships. It seems as though the focus has moved from establishing relationships to being in poor relationships. Topic 0 of the pre-COVID-19 dataset is labeled ‘Mental and physical Health Issues’, because the posts solicit advice for handling relationships where one or both parties are suffering from mental or physical health issues. For example, the post with the highest distribution probability expresses guilt for ending a relationship with someone suffering from mental health issues. One post asks how to help a friend with an eating disorder, and another asks for advice on supporting a significant other with chronic pain conditions. However, the post-COVID-19 Topic 0, which is labeled ‘Arguments In Romantic Relationships’, focuses more on losing relationships. For example, the top two distribution probability posts describe guilt after saying hurtful words in a fight. There were two other posts that describe gaslighting in an argument, and another post describing an argument over betrayal. There is also more evidence of social recession in the post-COVID-19 dataset than the pre-COVID-19 dataset. Topics like ‘Argument In Romantic Relationships’, ‘Poor Communication’, ‘Relationship Conflicts’, ‘Conflict In Living Situation’, ‘Betrayal and Confusion’, and ‘Relationships That Destroy Other Relationships’ suggest a fraying of social bonds.
The possibility for future work is the main purpose of this analysis. We questioned how interpersonal relationship dynamics are being measured and propose a new way of identifying these dynamics to create tangible resources for people in relationships. Although the results are not quantitative, the qualitative nature still provides a robust way to highlight the effects of massive social change. This topic modeling method can be applied to other subreddit communities or online forums as well. Even though we excluded demographic information from our analysis, these variables can also provide a way to create more intersectional resources. Another approach could also be considering the correlation between Topic Models and number of comments (which is provided in the dataset). Changes in our interpersonal relationships are not always in our control, nor are they always a bad thing. Understanding how we interact with each other and our environment can give us a better understanding of who we are as individuals too.
