The studies presents to us Themail, a program that gives users typographic visualization based off past emails. The team set out to answer two questions: what things does the individual talk about on email and how do their conversations differ across different people. They parsed their words and built two categories, yearly and monthly words. Yearly words revealed most used words over entire year of email exchange while monthly words were the most frequently used in an email conversation over a month. From that they developed two interaction modes for the user to explore with, haystack mode vs needle mode. The first dealt with trying to gain a big picture visualization of the relationships the user had, which most of the times the user already known. However, the needle mode served the purpose of finding specific information, which actually revealed information the user may not have been aware of. At the end, the majority of participants used the “haystack” mode to see their relationships between family members and friends. Alternatively, the users that used Themail in “needle” mode used it more to find work related information.
While reading about analyzing relationships via the context of messages, I thought about what kind of results this project would have if it was targeted to romantic couples. However, instead of parsing their email history it should parse their cell text history, for obvious reasons. The study should examine a couple’s text history from the beginning stages of dating until the couple splits or divorces. For couples that have been together for five, ten, fifteen, years, perhaps it’d be good to build a dataset of common words or phrases these couples use and compare them amongst each other with respect to how long they’ve been together. From that, perhaps researchers can build some kind of predictability models for any other couples as they would have plenty of data to compare against it. Does this couple, based off their messaging history, have a greater chance of staying together or breaking up in the near future? The only challenge to this is most people wouldn’t be open to freely grant access to their messaging history.
The difference of words used between same-sex vs opposite-sex messaging?
Would this study yield the same result if it’d done for other languages?
