In line with its interdisciplinary status within the University of Toronto’s iSchool, KMDI continues to evolve and improve with the addition of innovative faculty members. Dr. Jeffrey Boase, who joined the faculty earlier this year, graduated with his PhD in Sociology from U of T in 2006 and spent two years as a postdoctoral researcher in the Department of Social Psychology at The University of Tokyo.
We recently had the chance to learn more about Dr. Boase, his research projects, thoughts on our ever-evolving world of technology and his time so far with KMDI:
You joined the University of Toronto’s iSchool in 2015. What encouraged you to be part of it and the faculty of KMDI?
I’m very interested in interdisciplinary work. Although I was trained in sociology, I did a pre-doc in a school government, a postdoc in a social psychology department, and I worked as a faculty member in two communication departments before coming to my current position at the University of Toronto. I think this is because I tend to be interested in particular questions and use whatever methods and literature I feel best address those questions. I’ve always been interested in reading broadly and coming at problems from different angles. Although this is a risky strategy to take early in a career, it can lead to novel findings that can be of interest to broad sets of scholars and the public more generally.
Your most recent project is called “E-Rhythms During Adolescence, 2013-2017” and your main objective is to gain a multifaceted view of adolescent peer bonding through mobile phones and its consequences in social capital. The study makes use of a data collection technique that “triangulates smartphone log data, on-screen survey questions, and in-depth interviews.” What are some impressions you have considering the research findings so far?
We have not yet collected data. The first two years of the project have been focused on developing software that will we will use to collect and analyze the data.
The data collection software has been designed to collect non-identifying information about how respondents use their mobile phones to call and send text messages. This information can be emerged with survey questions respondents answer on-screen. For example, the software could identify the name of the person who they call the most. If this person was named “Jerry” in their address book, then the question could ask something like, “is Jerry a close friend of yours?”. Neither the name “Jerry” nor Jerry’s phone number would ever copied or stored to our database — the information that could be used to identify Jerry will always remain on the respondent’s mobile phone. However, using this method we will learn how mobile phones are used to maintain relationships of different kinds. We can do things like examine fluctuations in the relationships over time in terms of how frequently individuals are called the text and how often how regularly, and relate this to the information that we gather from the on-screen survey questions about the nature of these relationships.
The data collection software can also be used during in-depth interviews. For example, the app could select an individual for which there has been at least 20 text messages exchanged in the past week. It could then display the name of this individual on the respondent’s screen during an interview. Without hearing the name, the interviewer could then asked a series of questions about this individual to get some general understanding of who they are. Once again, throughout this process, neither the interviewer nor the software would record the name of the person that is being texted. Nevertheless, this approach will still allow us to gather a lot of really useful information about how text messaging is used to maintain different kinds of relationships.
We will commence data collection this year. I’m really excited to see our new system in use and learn more about how mobile phones help people maintain the many kinds of relationships that make up their personal networks.
In the last twenty years, the internet has revolutionized the way many communicate and live their daily lives. With mobile phones, the interaction with the internet is most times a seamless reality. In your research focus you are also interested in how smartphones and social media platforms may enable or hinder the transfer of information. To what extent, and how, are social media platforms hindering the transfer of information and support?
That is a very good question to which there is no simple answer. The short answer is that this is still a topic that is being researched and findings vary depending on the context and the method used to collect the data. However, results from my previous studies have clearly shown that although people tend to communicate with their personal networks using a wide variety of technologies, they may focus on particular technologies depending on the type of relationship. For example, text messaging tends to be mostly with individuals that are close to us, such as our friends and family. We still see our friends and family in person on a regular basis, but we also text message them heavily. By contrast, voice calling can be with a wide variety of people, some of whom are close to us and others that are not. So it seems that there is an interesting phenomenon whereby people actively drawing on many different types of media for all the relationships, yet they still tend to favour particular types of media for particular types of relationships.
What have you enjoyed about the institute? What need do you see KMDI filling within research about the relationship between technology and human daily living?
At this point I am quite new to the Institute. In my limited time here I have enjoyed learning about the wide variety of work being done by KMDI faculty members. I look forward to learning more and finding connections between my work and the work of other faculty members and students.
Dr. Boase will be teaching KMD1002H: Contexts and Practices for the winter semester of 2016, so look for him there next!