2023-05-10 12:57:00
A manager who doesn’t invite someone for an interview? Sometimes it is due to a bad feeling about someone’s name. ‘Computers can predict which associations people have with names and sounds,’ explains former data science student Aron Joosse in his Master’s thesis.
Where did the inspiration for your master’s thesis come from?
‘I went to an examination inspection of a course. Because I had obtained a good grade for this course, the lecturer asked me to write my thesis under his supervision. I wanted to do that. He then sent me literature on subjects he was involved in, including sound symbolism.
‘I have an affinity with language and culture and like to learn more about it in my free time. The choice to write a thesis about language, language associations and algorithms was therefore quickly made.’
What is your thesis about?
‘In my thesis I research sound symbolism. I look at what associations people have with certain sounds in names and words. An interesting area of research because sounds in names and words influence people’s choices. For example, think of a manager who does not invite someone for an interview because he has a bad feeling about a certain name. That’s very sad, because that gut feeling doesn’t have to be right.
‘In my thesis I don’t question people, but I see whether computers can guess what associations people have with names and words. I use algorithms. That way you can find out very quickly what association people have with a certain word.’
How did you handle that?
‘I model how people view certain names: do people think a certain name sounds masculine or feminine? Do they associate a name with a certain age group? Does this sound evil or sweet?
‘Take the fake names Brazarogh and Liselia, for example. When you ask people what name suits a monster and which name suits a little girl, the largest group of people will associate Brazarogh with the monster and Liselia with the little girl. Both names are made up. It is very unlikely that anyone knows them. Yet most people share the same connotations. That can be explained by sound symbolism.’
What is the outcome of your research?
‘The results show that algorithms are surprisingly good at predicting the associations people have with names and words. In my research I used the algorithm ‘FastText’. This algorithm is part of a family of algorithms that can learn what a word means by looking at the context of a sentence in which the word occurs. For example, think of coffee. Sentences containing the word “coffee” also often contain words such as morning, drink, hot, and caffeine.
“You could do the same for ‘beer’, which is often associated with evening, booze, cold and alcohol. By analyzing a large number of text files, the computer makes a lot of connections. This makes it understand that beer and coffee are related as both have an association with the word ‘drink’. But it also knows that they are not the same: the times and temperatures are different.
This information is super handy. In the future, algorithms can be used to recognize and predict biases in (online) communication. This type of research is still in its infancy and is currently not being used. In addition, authors and screenwriters can use algorithms to come up with names that suit their characters well.
‘Finally, companies can use algorithms to create brand names that fit well with their products and services. In this way they can prevent the association that the name of a product evokes from not being in line with the actual experience.’
Do you have any tips for aspiring thesis writers?
‘Before you start working on your thesis, take the time to explore the literature on your subject. That makes it much easier. If you understand from the start what kind of research field your thesis is in, it will be easier for you to keep an overview. So ask your thesis supervisor for literature tips.’
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