When playing online video games it’s common to run into strangers with unique names such as BongHit420, Unicorn Bae, and Goeasyonthekids. This is no exception to multi-player online battle arena games (MOBAs) such as League of Legends. Athanasios V. Kokkinakis, a research student at the University of York, decided to conduct research asking if usernames in League of Legends determined the social behavior of their users. After conducting the research with his colleagues they discovered that the usernames have at least two attributes that relate to their in game behavior.
These being the player’s age and their strong anti-social words (ANT) founded within their username. Their research paper “What’s in a name? Ages and names predict the valence of social interactions in a massive online game” was then posted in the 55th volume of Computers in Human Behavior. Kokkinakis is able to inform psychologists about the use of mining large datasets by using different rhetorical strategies in their text about their research on the connections between usernames and behaviors in video games.
One of the strongest rhetorical methods Kokkinakis and his researching team have is their ability to have a large amount of ethos in terms of credibility to the authors and their sources. Athanasios V. Kokkinakis and Alex R. Wade both come from the University of York. Both have had previous publishes to other scholarly sources. Wade in particular is also a professor at the University of York with a BA in Natural Sciences and a PhD in Neuroscience. Jeff Lin and David Pavlas on the other hand work for Riot Games. Riot Games are the video game publishers of League of Legends and the esports tournament organizer that was made in 2006.
This is a huge source of credibility for Kokkinakis and Wade because of how Lin and Pavlas work for the company that they did their experiment on. They also reference many other scholarly sources. The most common one of these is another addition from the journal Computers in Human Behavior titled “Personality and behavior in a massively multiplayer online role-playing game” by Narnia C. Worth and Angela S. Book. Both Worth and Angela work in the department of psychology at Brock University. Their work is referenced throughout Kokkinakis to back up his statements and results.
There are also 54 other sources that are referenced to Kokkinakis work that shows his readers that their text can be accurate and trusted. Kokkinakis uses these sources and studies to create a journal-style scientific paper that would express the experiment that they conducted. The text itself is split up into categories followed by subcategories with each category needed to make a journal-style scientific paper: abstract, introduction, methods and materials, results, discussion, acknowledgements, supplementary data, and references.
This is done so that the text can be set into sections and become easier to understand what each paragraph is dedicated for. It can also be classified as an experiment. Kokkinakis includes that they “hypothesize that if players’ real-world personality types predict their behaviour within the game, the valence of these interactions might correlate with factors that are related to real-world behaviour. ” Along with the hypothesis he also includes the procedure and the end results to their experiment.
Within his journal-style scientific text Kokkinakis focuses his text towards those who are interested in the psychological aspects of people when it comes to pc gaming. This is shown within the introduction of his text while explaining how MOBAs require strong communication between the team members to complete different team goals and allow individual objectives to be completed. He goes on to say that the communication needed to play MOBA’s represents “a rich potential source of data for psychological investigation”.
This in terms of audiences grabs the attention of psychologists who would be looking for stronger sources when it comes to people and communication. Kokkinakis puts his focus towards psychologists to inform them about the possibilities of mining large datasets for scientifically relevant relationships. He expresses when it comes to mining for relevant relationships that “if players do seem to exhibit systematic differences in behaviour, it might be that some of this variance is linked to real-world characteristics such as age, gender or personality”.
Kokkinakis goes further into supporting this saying that it could give more valuable information to researchers when it comes to large amounts of the gaming population. There is also in a sense a demonstration of knowledge to this alternative way of going about researching gamers. Throughout the article after the introduction Kokkinakis and his team of researches demonstrated and documented their way of mining large databases with their experiment that they conducted.
Not only did they do this throughout the text, but they show this with great success and results which in terms of the audience can persuade them to use this method of research as well. When demonstrating this method they also provided the rhetorical appeal of logos to their text. Their end results showed the statistics of how gamers were 25% more likely to be honored and 25% less likely to be reported if they didn’t have antisocially named accounts. Along with this they go on to talk about how older gamers were less likely to give or take negative reports then younger players.
In doing this Kokkinakis is able to prove to psychologists reading this paper that the results from this form of study can still give accurate answers and feedback to their research questions. For others who are into League of Legends or other MOBAs this also gives players information on how usernames in videogames can affect behavior and influence others to see them in a different way. Kokkinakis continues to emphasize his logos within the text through the use of different graphs and photos. The graphs used come in multiple formats to show off their findings such as rea charts, bar graphs, and scatterplots. Along with the graphs are screenshots from League of Legends showing some of the ways to communicate with one another and the honoring system. This can be important to show as some readers are more visual oriented rather than text oriented and will be able to understand it more than just reading the text of the journal. An example of this is seen when Kokkinakis and his colleagues explain their methods and results of the similarity between usernames with numbers in them and the ages of those players when they registered.
At first glance the information can be seen as confusion when trying to read off the numbers. However, when looking at the figure 2a charts it becomes clearer to see that the usernames and the estimated birth years become more common and accurate as you go from the year 1985 to the year 2000. Another method that is used to help understand the text is the use of examples throughout the journal. Kokkinakis does this because his target audience may not be familiar to League of Legends.
One of these being the use of usernames such as Goodplayer1996 and Goats3x to show what kind of usernames were reviewed and used in their controlled group. An example of this comes from their explanation of the false positive usernames that were rejected. Kokkinakis explains “Out of the 3229 hits in the North American Server, 1031 nicknames were rejected as false positives after visual inspection by an expert English speaker who was blinded to the statistics associated with each name.
For example, there would be nothing deliberately anti-social about the name “ThePen1s Mightier” despite it generating a hit in the swear word dictionary lookup”. Being given these examples help clear up any sort of confusion for psychologists. Making the text easier to them to comprehend and understand. When looking through ‘What’s in a name? Ages and names predict the valence of social interactions in a massive online game” you can clearly tell that much work was put into the text.
Throughout the journal Kokkinakis and his group of researchers showed not only the connections between player’s usernames in MOBAs and their in game social behavior, but they also were able to demonstrate and conclude their hypothesis of “whether psychologically interesting information could be obtained purely from a large, anonymized gaming dataset”. Kokkinakis and Wade were able to work hand in hand with Lin and Pavlas to create a strong and credible journal-style scientific paper. Their focus on psychologists was developed in the beginning of the text which made the topic clear and interesting to read to his intended audience.
Finally the authors were able to back up their hypothesis and evaluation with accurate uses of logos such as the use of examples to make the text more understandable, graphs to give clear visual representations to the text, and statistics to show the readers that psychologically interesting information can be obtained from mining a large group of gamers. The combination of all of these elements gives Kokkinakis and his partners for this text a strong and effective article that can be easily interpreted, even to readers that do not have a clear understanding of MOBAs such as League of Legends.