In order to find information from the city to answer these research questions, we used a variety of research tools. Specifically, we utilized 26 in-person qualitative interviews at the Hartford Public Libraries (Downtown branch and Park Street Branch) to hear stories and understand how some people in Hartford receive their information. As well as in-person interviews, we created an online survey (HartfordInformationalServicesSurvey) that we sent out through social media platforms, mostly Facebook, to learn more of what communication strategies work and don’t work. In doing so, we collected 39 Hartford surveys and 27 non-resident surveys ( Total Survey Data.xlsx ). This set a baseline of what services are known and being utilized. The more residents that we reached out to, the more effective our project, data, and future advice would be.
We then took both sets of data from the surveys and in person interviews and coded most questions to quantify the data. This allowed use to interpret and visualize the data.
We decided to use both methods in order to vary the type of data collected and vary who we got responses from. With conducting different types of data collection, we then used triangulation to analyze the data from different angles to better understand what causes the distance between the residents and the city. We knew that not everyone in Hartford has internet access, and even if they do, the only method we had of distributing the online survey (social media blast) would mean we would only collect responses from people connected to our social circle.
Our goal was to hear from as representative a sample of Hartford residents as possible, which is where the in-person interview method of data collection helped. We hoped that conducting both in-person interviews and distributing an online survey would also diversify the type of data we collected, as we wanted a mix of both qualitative and quantitative data. We were really interested in looking at the qualitative side of the data (like why Hartford residents are unsatisfied with city communication and what are they unsatisfied with exactly), but we were also interested in finding how much dissatisfaction exists within the city, and looking for trends or patterns in our data. Using a mixture of both qualitative and quantitative data was a good choice for satisfying all our goals.