Recently in one of my Social and Information Network lectures, we discussed the idea of Structural Balance. This was essentially the idea that if a network had signed edges (positive or negative), then we could classify the network as stable depending on the patterns every triangle that was made with the signed edges made.
Since the usual example that was used for our networks was social networks, it was easy to see this representation as a social network of people, where the signed edges either meant two people liked or hated each other. In that case, a triangle with only one positive edge would represent two friends who both hate the person, and a triangle with only one negative edge could represent a love triangle, where two people are competing against each other for the love of the other person.
When I pointed the love triangle case out in class, I got a few laughs. The professor ended up stating that the love triangle case is also not stable. Although it is strange and possibly funny, I do find it interesting that we could use graph theory, and other course content that we learnt in class, to analyze the different structures that may come up when analyzing relationships in a drama for example. Maybe it’s possible to analyze a drama episode by episode, mapping out the relationship network to predict interpersonal conflict between the different characters depending on the stability of the triangles. Since love triangles are a common plot device, maybe you could even use this to predict what happens next episode, if the negative and positive edges indicate the intensity of the relationship between two nodes.
I then decided to search around for articles around this concept and found this one. It’s not super recent (2015), but here they trained a neural network on the TV show “Friends”, (the scenes and the subtitles). From that, they were able to generate this affinity chart.
Admittedly, I’m not 100% sure of how they generate this chart, but it’s neat that tracking this is even possible. I wonder if this can also be used to predict how countries interact with each other. I did find another paper that measures international relations by the use of social media, but given the use of bots on social media, I decided not to look further into it.