How Relevant is Homophily in Dating?

In class, we covered the topic of homophily and how it relates to the age, friendship count, and nationality of connections on Facebook. As expected, we found that the more people have in common with each other, the more likely they are to be friends. This result was obvious when looking at the race distribution of students in middle/high school, where students of the same race were more likely to connect with each other than with students of a different race. The phenomena of homophily in social networks, as seen in class, is applicable to many areas in life and is especially interesting when considered through the lens of dating.

In a study conducted by MIT, psychologists found that the more similar two potential romantic partners are, the more attractive they would be to each other and the more satisfaction both partners would have from their relationship (Fiore, Andrew & Donath, Judith, 2005). The study, conducted on an online dating site, showed that users selected partners with similar characteristics more often than chance would predict, which holds true for all of the characteristics that were analyzed. Moreover, the study found that users were more likely to respond to an initiation by a user that shared similarities with them.

Table 2 shows the characteristics that were evaluated in the study. An actual sameness percentage close to the expected sameness percentage indicates that users who communicated with each other with the shared characteristic did not communicate as often by chance as the researchers would have expected. A greater difference indicates that the users who shared a similar characteristic communicated much more often than expected.

The three most similar characteristics ( > 50% actual percent same) among people who found their partner on the dating site were: race, drinking habits, and marital status. The three least similar characteristics ( < 50% actual percent same) among people who found their partner on the dating site were: pets owned (not surprising), physical build, and education level. Keep in mind that the values for these characteristics are simply a measurement of the percentage of users that shared a characteristic; which is different than measuring which characteristic users found most attractive. In other words, a user in this system is more likely to date someone with a similar race with a less attractive physical appearance than date someone who is more physically attractive of a different race. 

These findings show a clear indication of homophily in the dating scene, which means that if you want to have a better chance at standing out to your crush, your best bet would be to explore the similarities that you share with him/her.

Links:

https://www.researchgate.net/publication/221518104_Homophily_in_online_dating_When_do_you_like_someone_like_yourself

Further discussion:

https://www.nytimes.com/2006/12/10/magazine/10Section2a.t-4.html

Reference:

Fiore, Andrew & Donath, Judith. (2005). Homophily in online dating: When do you like someone like yourself?. Conference on Human Factors in Computing Systems – Proceedings. 1371-1374. 10.1145/1056808.1056919.

Fake News and Its Cascading Effects

The topic of false and distorted news has been a part of our history for thousands of years. The underlying motive behind the spread of false information is to sway the opinion of people to achieve some goal. In recent times, the term “fake news” has made its way into common everyday vocabulary due to its prevalence in Western culture, particularly in Western politics where certain groups defame political parties to influence the outcome of elections. The cascading effects of fake news in society is extremely relevant to our course material as it is a topic that can be examined through the flow of information networks to understand how fake news becomes viral. This blog post will discuss the following questions: How exactly does fake news spread? Is there a way for social media platforms to eliminate the spread of fake news?

Fake news is spread most effectively through social media platforms, such as Facebook, Twitter, and Instagram. The spread of fake news is typically done through bots, and “According to an estimate in 2017, there were 23 million bots on Twitter (around 8.5% of all accounts), 140 million bots on Facebook (up to 5.5% of accounts) and around 27 million bots on Instagram (8.2% of the accounts)” for a total of 190 million bots on the three platforms combined. The bots reach a large audience by flooding the platforms with false information through trending topics or hashtags, to gain publicity on their posts by being recognized by the platform’s relevance algorithm. With countless bots simultaneously relaying the same false information, naïve audiences often tend to believe propaganda and further spread the lies themselves, creating a cascading effect.

Information flows through social media platforms at an alarming rate. The more connected people are in their networks, the wider the reach of the information, as shown in the picture above. This makes social media platforms the prime target for the spread of fake news.
The network visualization of the spread of the #SB277 hashtag about a California vaccination law, where the nodes are twitter accounts posting with the hashtag, and the edges between them show retweets of hashtagged posts. Red dots are likely bots, and blue dots are likely humans.

Can social media platforms prevent the spread of false information? Miriam Metzger, a UC Santa Barbara communications researcher says, “Fake news is perfect for spreadability: It’s going to be shocking, it’s going to be surprising, and it’s going to be playing on people’s emotions, and that’s a recipe for how to spread misinformation”. The natural attractiveness of fake news to the human mind means that fake news will always manage to trend in some way. Platforms such as Twitter can use false information detection algorithms to help with reducing the flow of fake news by creating true and false information models and act on their platforms accordingly. However, the issue of fake news arising in social networks will never be eliminated entirely because of the emotional responses generated from them.

Relevant links:

https://www.vox.com/science-and-health/2018/3/8/17085928/fake-news-study-mit-science

https://www.cits.ucsb.edu/fake-news/spread

https://arxiv.org/pdf/1804.08559.pdf

https://www.cits.ucsb.edu/fake-news/brief-history