Cybersecurity Challenges in Social Media Erdal Ozkaya

5.6
 
Survey instrument 
The questionnaire was administered using Google Forms, which would capture and 
return the collected data in real time. The questionnaire was comprehensive and ensured that 
all the topics of interest to the research had been covered in the questions. To access the 
survey, a respondent had to view it on a browser. Google Forms was the most ideal as it 
supported the use of many data collection tools, such as radio buttons and checkboxes. It was 
also more mobile friendly and had no display issues on the respondent’s devices. Since the 
forms were not scripted, there were no errors arising from the failed capturing of data.
Google Forms was also effective in breaking the entire questionnaire into tiny and 
related bits. Users would submit the questionnaire in parts; thus, they were not discouraged 
by its actual length. The breakdown of the survey into bits also made it appear to be more 
streamlined and focused on a particular issue at a go. The distribution of the questionnaire 
was done through Gmail. The respondents were not required to have a Gmail account in order 
to access it; they were only required to visit the link sent to their emails and access the 
questionnaire. The details about the respondents that received and completed the 
questionnaire were not stored. This is because such action would have to be treated as private 
information and thus require more security for storage. The Google Forms form was set to be 
completed in guest mode. Therefore, the users would not later on be identifiable; only the 
data submitted on the forms would be received. The senders’ addresses were not recorded in 
this mode as well. 
5.7
 
Statistical analysis 
Data collection was done using Google Forms and the analysis part completed in 
Microsoft Excel. The data obtained was mapped back to the questions and then, the analysis 
was done. The collection of the data using Google Forms was such that the collected data 

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would be easy to formulate findings. From the raw figures, percentages were calculated to 
help make more sense of the data. The raw numbers were the actual number of respondents 
that gave a certain answer. From the total responses, the calculation of responses was quite 
simple to achieve. 
In some instances, data had to be cross-tabulated in order to arrive at finer details. For 
example, if it was of interest to find out the number of particular respondents in a subgroup 
that gave a certain answer, cross tabulation would be done. Mostly, cross tabulation was of 
use when correlating the respondents’ age, education level, and literacy level to certain social 
media usage tendencies.
Codes were also used in the statistical analysis of data. Since the data collection was 
qualitative, this type of data was not ready to be analyzed. Therefore, codes had to be used to 
convert the data into values that could be analyzed. For example, questions that asked users 
to rank their most and least used social media platforms had to be codified so that this data 
could be analyzed. 
Charts were used to display the data in a richer and more appealing graphical format. 
This data would be drawn from the Google Forms backend and then carefully mapped into 
pie charts, bar graphs, and line graphs. Graphical representation helped to easily interpret the 
responses derived from the respondents. Graphs could readily tell the trend of responses and 
also discuss better the story that the data was telling.