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Thursday, December 19, 2024
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EFFECTS OF ONLINE COMMUNITIES-A RESEARCH STUDY

EFFECTS OF ONLINE COMMUNITIES-A RESEARCH STUDY
EFFECTS OF ONLINE COMMUNITIES-A RESEARCH STUDY

ABSTRACT. The purpose of this prospective cohort research study was to test the hypothesis that online and social media community has an effect on our day to day and it creates ties that bind and attachments of individuals who are mutually aware of each other. The Internet is such a strong and an amazing tool. But even as itโ€™s shrunk the world and brought people together, it has also threatened to push us further apart. We identified current events that created huge responses in the online community and those that drew more Internet traffic on daily basis. For this study, we narrowed down to the recently just concluded presidential elections in Kenya, Eastern Africa on 10-26-17. We selected Facebook platform as our population .We generated and analyzed data statically from 20 private Facebook accounts. We concluded that the research study was successful. However the sample was relatively small and not enough length time definitive conclusions but it served as a prototype to other researchers who may want venture in such studies.

INTRODUCTION. The Internet is such a strong and an amazing tool. But even as itโ€™s shrunk the world and brought people together, it has also threatened to push us further apart. [1] According to Alex Lickerman, like any useful tool, to make technology serve us well requires the exercise of good judgment. A tool is only useful if it is used appropriately. For whatever reasons we just donโ€™t feel like the Internet and many other typed form of communications have the same power to do harm and kill relationships as when we verbally rely them face-to-face. It is far easier for us to bully and say meaner and hurtful things and interferes with other peopleโ€™s feelings online than do it in person. The Internet and social media have combined to create a vibrant and indispensable communication and information platform and infrastructure for todayโ€™s World. More over the Internet has not only had effects on real-life but it has also created communities in the online world- more so to speak cocooned family links. People tend to identify and defend groups of the same interest and choose to identify, recognize and get affected but the information they see online as part of their real life norms. Online communication is not seen as a separate realm anymore [1]. If people feel the kind of information they reading online is more skewed to their belief and worldview, they tend to form a connection with that information and without knowing, they form a bond and creates an online family that grows to a wider community and eventually tend to shunt out any other group or โ€œfamilyโ€. The purpose of this prospective cohort research study was to test the hypothesis that online and social media community has an effect on our day to day and it creates ties that bind and attachments of individuals who are mutually aware of each other.

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METHODS. We identified current events that created huge responses in the online community and those that drew more Internet traffic on daily basis. For this study, we narrowed down to the recently just concluded presidential elections in Kenya, Eastern Africa on 10-26-17. We selected Facebook platform as our population. We then selected 20 private active Facebook accounts that had huge followers and that posted the current events in Kenya during pre- and post election timeline as our samples. The platforms had to have at least a single post daily 3 days before the elections, during the elections and 3 days after the elections. We identified the platforms in association with the two main political parties in the region and categorized as group 1: Jubilee party affiliated platforms and group 2: National Super Alliance affiliated platforms. We then followed the postโ€™s responses and grouped likes, smiley faces, hearts emojis and good comments as positive responses. We also grouped bad comments, angry faces and tears emojis as negative responses. Group1 had 10 Facebook accounts and group 2 had 10 accounts respectively.

We also performed a separate Placebo controlled trial on the population using our private Facebook account (Gits Wairimu). For this placebo we affiliated the account with group 2. We felt that affiliating the account with group 2 was highly important for the placebo control in avoiding bias through association. We posted comments that favored group 2 ideologies on the account. We would then post favorable photo of the accountโ€™s owner 8-10 hours after the posts, accompanied with comment that was not related to either group 1 or group 2. We repeated that on day 1,day 2, and day 3 before the elections and day 1, day 2 and day 3 after the elections respectively. We then retrospectively went through the comments, likes and emojis on the placebo. We grouped good comments likes, smiley and hearts emojis as positive responses and bad comments, angry faces and tear emojis as negative responses respectively.

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Inclusions & Exclusions. We included Platforms that posted on daily basis. Accounts with verifiable names and had to be individual accounts. We excluded accounts that were corporate or Government ran agency. We also excluded accounts owned by political figures or government agencies. We then excluded comments that were directed as insults or those that we could not determine whether positive or negative. Comments that were in other languages besides Kiswahili and English were also excluded, as they would not be verifiable, lacked translations or lost translation.

RESULTS. We generated detailed statical graphs of Group 1 and Group 2 samples, and the placebo responses respectively and recorded the data as shown on figures 1 and 2. Group 1 received 18,032 responses. 1989 of those responses were negative responses, which constituted 11% of the total responses while 16043 were positive responses that constituted 89% of the responses. For group 2, we recorded 22044 responses with 2967 negative responses and 19077 positive responses. This constituted 14% and 86% respectively. The placebo received 2100 responses for posts with 900 negative Reponses and 1200 positive response. That constituted 43% and 57 % respectively. The photo responses recorded were 780 with a 100% positive response.

Figure 1. Group 1 & 2

ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย ย  ย Figure 2. ย PLACEBO

DISCUSSION. From the study, we determined that individuals join and follow online platforms and communities who are like them in terms of opinion, experiences and identities. For instance a post from group 1 that sounded more supportive of the same group would generate more positive responses from members of the same group and few negative responses from group 2. This would also trigger the same responses respectively in members of the same group when the post is diminishing the rival group and vice versa. We also determined that a majority of responses whether positive or negative would come from the same individual. For instance if a certain account posted a comment, the comparison of responder on that particular post would be between 80-85% match with the responders who responded on the previous post in the same account and would still be almost or exact same percentage match if another post follows. We realized that it was possible to predict who would respond to post even without looking. This is an indicative of online imaginary community identity that give individuals a sense of belonging and the urge to want to respond or defend that imaginary community or leader every time they post a comment. Eventually it may end up making it an obligation and or even an obsession to always want to respond to every post that is posted in that account. Mentally it makes the individual feels obliged to always respond to post in that platform. If they donโ€™t respond it makes them feel like they are offending the one posted it. While going through the placebo we determined that online community is mostly effective when dealing with disagreement or thing that donโ€™t agree with a certain group on when the groups donโ€™t know each other in real life and have not actually met. For instance if a post appeared on the placebo that happened to diminish group 1

 

or praise group 1, the responses both positive and negative would come from individuals who donโ€™t personally know the platform owner. This is because individuals had already developed a sense of belonging and an imaginary community that dealt with their interest and hence felt it was necessary for them to defend in unity, their own interest. On the contrary, the responses of a photo posted on the placebo platform (Gits Wairimu) would get a totally different group of individuals who appeared to have mutually same interests in the real life. About 80% of responses would be from individuals that are relatives, real life friends or at some point have interacted with the platform owner in real life. We also discovered about 75% of the individuals who responded to a photo post would not respond to comment posts. This indicates how its very possible for people to ignore opinions they donโ€™t like or disagrees with and even more saw if the Know the one posted in real life. People that know you in real life would rather ignore or declined to comment on things they donโ€™t agree with or dislike to avoid frustrating and hurting your feelings at an expense frustrating their own emotions.

 

CONCLUSION. ย It is very possible for individuals to get addicted to information coming from the same online source whether the information hurts or builds their feelings. Once one gets exposed to the information it becomes a myopic norm. The source then can start controlling whoever gets addicted to the information. Eventually the source will become the only trustable source of information and a leader and in the event that the source of the information producing inaccurate information this can be catastrophic. We concluded that the research study was successful. However the sample was relatively small and not enough length time definitive conclusions but it served as a prototype to other researchers who may want venture in such studies.

REFERENCES.

[1] “The Effect Of Technology On Relationships.” Psychology Today. N.p., 2017. Web. 3 Nov. 2017.

We also want to acknowledge and thank the following Facebook platform account owners who allowed us to references their accounts on this study. Data was collected on all 20 accounts. All the account owners were notified about the study. Not all accounts owners responded or accepted to be referenced and acknowledged. Those who did not respond to our request or declined to be referenced will remain anonymous:

  1. Moza Moses K/facebook.com
  2. Mwika w aka-yes/facebook.com
  3. Kemunto Bitutu/facebook.com

4.Missthang Akinyi/facebook.com

  1. The Jay/facebook.com
  2. Kiprotich Dโ€™Keidza/facebook.com
  3. Kijana Wa Yesu/facebook.com
  4. Gits Wairimu/facebook.com
  5. Anonymous [9-20] /facebook.com

By John G. Wairimu |MS. Sci. Nuclear Medicine| B.S Public health

jgitau5@uab.edu jgitau5@yahoo.com

 

EFFECTS OF ONLINE COMMUNITIES-A RESEARCH STUDY

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