Scientific Article Analysis on Facebook

492 words | 2 page(s)

The article, Is Facebook use causing people to get divorced, suggests that using Facebook for more than one hour per day will cause relationship instability that leads to higher divorce rates. The assumption is that Facebook use is specifically correlated with higher divorce. However, there are potential alternatives for this observed correlation: first, that people who use Facebook frequently may already be experiencing relationship problems, so heavy Facebook use is a symptom of relationship instability, and not the cause; and second, that Facebook is a potential time-sink that takes away from quality time for a relationship, but that Facebook specifically is only one possibility. Correlation means there is an observable connection between two phenomenon, such as Facebook and divorce, but does not necessarily mean causation. Causation is where one phenomenon directly causes another phenomenon, such as Facebook leading to divorce.

The intangible independent variable is Facebook use among experiment participants. The dependent variable would be divorce rates. Conceptually, I would be testing whether engaging with social media activities, particularly Facebook, causes an increase in divorce rates. Facebook use would be operationalized as time spent viewing posts and interacting through comments and messages, as well as time spent checking notifications, and then I would compare the amount of time people spent on Facebook with divorce rates.

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The hypothesis being tested is: The amount of time spent on Facebook has a positive correlation with higher divorce rates. The null hypothesis would be: Heavy Facebook use increases the risk of divorce.

In order to conduct this experiment, much of the data would need to be collected through a survey, as Facebook use cannot be controlled or directed. Thus, the primary participants would be surveyed on their own typical Facebook use. They would then be surveyed in regard to marital satisfaction, with low satisfaction indicating an increased risk of divorce. However, because one of the potential problems with the experiment in the article is that it simply measures Facebook use, there would need to be another control group where any other activity was taking an equal amount of time out of one’s day. If the research is intended to analyze Facebook as a specific platform, then the experiment could also evaluate similar data from heavy users of Instagram, Twitter and YouTube to determine if Facebook correlates with higher divorce rates than these other platforms. The reason this aspect is necessary to determine a causal conclusion is because Facebook might not be the reason people are getting divorced; instead, it could be related to time spent on any activities outside the relationship.

One other aspect of this procedure that would help eliminate the risk of bias would be other social media sites could possibly be evaluated. There might be a correlation between Facebook and divorce rates, or there might be a correlation between social media and divorce rates, or a correlation between any activity that took more than one hour per day and divorce, regardless of type.

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