Pre-Theme 4: Quantitative research

Information sharing on social media sites

B. Osatuyi, from the journal Computers in Human Behavior, Impact Factor: 2.067.

 

Problem

 Credibility with information shared on social media sites.

Research design - quantitative methods

Data was collected using a web based survey with e-mail invitations. It was of exploratory type. 200 university students were e-mailed a link to the survey. Only 114 students gave complete answers, even though all participating students were rewarded extra points for their grades.

Five social media technologies were included: 

1. Social networking
2. Micro-blogs
3. Wikis
4. Forums
5. Blogs

The definition of each information type explored in the paper is backed up by references to other studies.

The study used the following categories for information: 

• Personal (sensitive); health, relations
• Sensational; news, gossip, science
• Political; political discussions
• Casual; restaurant reviews etc

Chi-square test was used to analyze the results regarding which media technology is used to share information. The appropriateness of this method is explained by the ability of estimating if two variables are independent. The Chi-square test needs an estimated value to be compared with the observed value. I did not find any such estimations in this paper.

The study also introduces a classification code that the participants may use to indicate credibility of the shared information on social media. It's on a scale between 1 and 14 and contains fourteen combinations of the following credibility indicators: 

• Link to other sources
• Topic of interest
• Embedded video
• Embedded audio

However, it does not include the familiarity factor. My immediate thought is that familiarity with the person posting the information will affect the credibility quite a bit. I think they could have referenced such study. I found one research paper from University of Alabama called " Factors and effects of information credibility" that could've been relevant. However that type of research might be of more qualitative nature.

Above methods were used to reach the answer to their first question, "Does the codification of information credibility vary across different social media sites?"

The second to fifth questions were about if information shared varies on different social media. The variance of the answers (ANOVA) seem to have been analysed by calculating the degrees offreedom.

The analysis methods for these questions were the same. An example: the result of the first question in this series was that there was no statistical difference on which social media site people share personal information. I find myself at loss at criticizing the method since I lack the proper knowledge about it.

Conclusion and What did I find and learn?

The conclusion from this survey was that there is a difference between how people share information on social networking sites compared to other social media sites. It also finds that people are careful with what personal information they share. The researchers argue that organizations may use this to better engage their customers.

I think that they could have found a way to contact a larger initial group of potential participants since not many answer surveys. From personal experience, I will often not participate if not interested. Maybe this is a weakness of the method, only very motivated people will participate. 

Though they seem appropriate, for me it was a bit difficult to analyze the statistical methods due to limited knowledge of statistics. I had to look up the basics of ANOVA, Chi-squared test and degrees-of-freedom, but would still benefit from attending a statistics course.

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Physical activity, stress, and self-reported upper respiratory tract infection  

Bälter et al.

Problem and Background

Many seek medical attention due to common cold and influenza (URTI).  The research focused on investigating the relation between URTI, physical activity and stress.

Previous studies of similar nature have been more qualitative and focused on smaller groups of athletes.

Research design

The study used a population-based prospective cohort method where about 1500 random participants were selected.

For the quantitative data collection, it used an adaptive web questionnaire, with E-mail reminders. It summarized the collected data from various questions, about health and lifestyle, automatically into points on MET-hour and Perceived Stress-scales, where MET is the rate of energy consumption.

The MET-hours were multiplied with reported hours spent on certain activities by questionnaire participants. There's a clear definition of how stress was measured with the PSS-scale.

Follow up questions on influenza-vaccine and allergies to rule out symptoms not related to URTI at the end of the data collection phase.

A clear diagram shows selection and filtering of random participants in for study. Nice tables are presented of the collected multi-variable data. Incomplete results were not used.

Discussion and Conclusion

The conclusion from the analysis was that physical activity lowers the risk of URTI for both sexes. It also states that highly stressed men benefit the most from physical activity. The study could confirm findings from other similar research regarding the relation between physical activity and URTI, except for one study example where the test group consisted of professional athletes. It could however not clearly confirm an overall relation between stress and URTI despite attempts to exclude/select parts of the data to make it fit previous findings. Though there was apparently a stronger relation between stress and URTI in men, perhaps because the way men react to stressful situations.

I think that they satisfactory discuss weak points in the data and explain why it probably does not affect the overall result. The conclusions can be useful in further studies, and as a resource in informing the public about exercise, illness and stress. I think that this was an excellent report and the scope is wide enough, I wouldn't change anything really.

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Which are the benefits and limitations of using quantitative methods?

From reading the research by Bälter, it seems that it's easier to get a result that represents the majority if a large and random group is studied. If the subject group is too small, the result may not be representative.  Also, occurrence of  phenomena may be missed out due to the focus on testing a hypothesis rather than producing one.

Which are the benefits and limitations of using qualitative methods?

Since the qualitative study selects a smaller group to study,  it can give a clear and detailed description on an individual and specific level. It can, as opposed to a quantitative study, react and change focus based on findings during the study. However, collection of data might be more difficult and takes more time, the results might not be applicable to other groups, and the result could be influenced by the researchers subjectivity.

References
University of South Alabama 2013,

Strengths and Weaknesses of Quantitative Research
Strengths and Weaknesses of Qualitative Research