Since the beginning of the year, we have started to finalize the project work because of the fact that we applied for the International Communication Association (ICA)conference. Intensified progress generated some problems associated with cleaning up the dataset, establishing new coding manual methodology, and therefore, appropriate coding which I found challenging and time-consuming.
First of all, me and my professor had to clean up the data set to prepare a fundamental database determining the quality of the subsequent coding. It was done by verifying each website’s advertising appeal in order to keep a consistency in the methodology of collecting the data set. For example, Badoo for Argentina has its Argentinian subdomain (Badoo.com/Argentina) but in Google search results, after typing “online dating in Argentina”, there was a link Badoo’s main website (Badoo.com). We decided to collect the adverting appeals from both sources. It is because of the fact that the subdomain targets specifically an Argentinian audience (therefore, the advertising message is adjusted to appeal to this nation). Moreover, we kept an advertising appeal from the main website, to be consistent with our rule of collecting what shows up in the Google search results (which is described in detail in the previous blogs). After we went through this long process of improving the data set, we started to do the same thing with the coding process.
Even though the coding methods (of the online dating services’ advertising appeals) were prepared few months before I started the actual coding while applying the concepts into practice, me and my professor, found out that we have some disagreements in how we understand the coding instructions. We determined the disagreements in the following way. We both coded the same sample data—consisting of 106 cleaned-up websites— on our own in order to compare the work by matching our coding. When we found any differences (in how we coded a website), we thoroughly discussed our reasoning and logic behind the way we coded it. Sometimes, it required us to change the coding specifications since they were too general or not applicable in practice.
Subsequently, when we clarified any disagreements, my professor let me code all the dataset. This part is still in progress. However, I already know that it is a very responsible assignment since my coding will be directly used for the analysis. Not only it requires me to work on it for not too long (to prevent myself from making mistakes) but also, I have to be very precise, consistent with the established methodology, and objective. It challenges me, but after putting much efforts into this work, I will be proud of the quality and reliability of our research findings. That is why I am even more motivated to act!
The work let me and my Professor ask the following questions:
- Which motivation is the most frequently occurring across all websites?
- Which motivation is the least frequently occurring across all websites?
- Which motivation occurs more in Europe vs South America vs North America?
The most popular motivation refers to the M7 (Motivation 7) which stands for the design of the website since most of the dating services talk about the fact that it is for free. The least frequently occurring one is M2 which stands for sex. It is astonishing for me because I thought that this category would be more commonly applied as a part of the online dating websites’ marketing. However, I have noticed that in the South American countries the visual and text appeals tend to be more sexually suggestive, whereas in the European countries the messages appeal by talking about family, love, or happiness. The US has the most hook up dating services but this number is still not as high as I expected it to be. Therefore, I am more and more excited about the ending results of the research since the analysis can reveal very astonishing information