Bots are specific fake accounts which are employed in networks of social media to generate messages automatically. Bots generally advocate particular ideas, public relations and support campaigns through the use of followers or fake accounts for the gathering of followers themselves (Hjouji, 2018). For instance, social bots are perceived to have significantly played a role in the 2016 election of the United States. Several sources estimate 9-15% of social bots to be active twitter accounts and 15% of the total twitter population that was active in the presidential election discussion of the United States were bots (Zaman, 2018). In the present times, social bots can give rise to internet persons that are capable of influencing individuals. Many social platforms discourage the use of social bots under their terms of service. However, most social platform users particularly the businesses still carry out automation to gain more followers (Hjouji, 2018).
1. News Article Purpose and Study Fit: What was the purpose of the news article and how does the research study contribute to that purpose? What makes this specific study newsworthy?
The United States' Conversation news articles aim at providing information on the effect of bots into the online discussions. Zaman, (2018), documents that bots affect the real people's views. According to the news article, approximately two-thirds of political activity social media bots on twitter before the United States 2016 presidential election Supported Trump. Nevertheless, these trump bots were less effective in shifting the opinions of the population in comparison to the smaller size of bots that backed Hillary Clinton. The major factor was not the number of bots present but rather the number of tweets each bot issued (Zaman, 2018). The research study presented the bots impact on the users' opinions. It focuses its analysis on 2016 presidential election discussions in the social network of Twitter users. The research utilizes the opinion model approach which firstly validates the model, then identifies bots in the system and finally calculates the shift of opinions in the absence of bots in the lead network. The findings dataset reveal that the bots that supported Clinton caused a more significant change in eopinions unlike those who supported trump (Hjouji, 2018).
The article raises concerns for future 2018 mid-term elections regarding how the bots are likely to affect the outcome thus newsworthy. The author opted to determine the influence of bots on political views of citizens through identification of social media bots and evaluation of their activity. The opinions of social media users are also taken into consideration (Hjouji, 2018).
2. What are the study’s most important details (method, sample, results)? Do NOT copy/paste from the article. Use quotation marks as needed. Be careful not to plagiarize accidentally.
The author and his students focused their analysis on discussions on Twitter around a single activity in the election old lead up. That is the second debate between Trump and Clinton. The study participants collected 2.3 million tweets containing hashtags and keywords concerning the debate (Zaman, 2018). Then they made a list of about 78,000 Twitter users that posted the tweets and developed a network of followers. To identify these bots, they used an algorithm regarding the observation that bots usually re-tweeted people but were not often re-tweeted themselves. The process found 396 active bot users whereby the accounts that followed them were 10%. Hence, it unlikely seemed that such a few numbers of disconnected bots could significantly change the views of people (Zaman, 2018).
The study further used a machine learning algorithm referred to as a neural network that evaluates the specific content of tweets hence finding out the extent of presidential candidate support. The research employed a data score representing the strength of each presidential aspirant despite a challenge in the calculation of how the people shifted their opinions. Finally, the researcher calculated the network model after removal of social bots from the network to determine the real opinions of people without bots. It revealed that bots had changed human opinions (Zaman, 2018).
3. If you were an author of the published research article, how would you respond to the news article? Did it objectively present the study, was any piece biased, what type of information was missing from the article that you think should have been included (e.g., missing results, limitations of the study)?
It is crucial to comprehend the bots’ impact on the views of social networks users. The method presented showed how the models of opinion dynamics the accomplishment of this. The model validated in regard to the content of users (Hjouji, 2018). The article evaluated different scenarios by removing bots from the social network. Hence, results showed that bots had disproportionate opinion effect. Trump bots had less effect on opinion than Clinton. Also, we found that Clinton’s bots. The article result suggests that a few numbers of active bots can significantly shift social network opinions (Zaman, 2018).
It’s of importance to note that the article's analysis concentrated on the small number of users in comparison to the voters in the United States. The study is biased in such a way that it was executed in a short period an around a specific campaign event. They fail to suggest anything concerning overall election results (Hjouji, 2018). They give data on the potential effects of bots on the opinions of people. The efforts of social media have not met a success yet on efforts to get rid of bots constantly tweeting to influence the voting population. The article ought to include different media platforms which bots are likely to be useful (Zaman, 2018).
Conclusion
Bots consist of specific fake accounts which are used in networks of social media to generate messages automatically (Hjouji, 2018). Bots generally advocate particular ideas, public relations and support campaigns with the use of followers. Social bots can give rise to internet persons that are capable of influencing individuals. The United States' Conversation news articles aim at providing information on the effect of bots into the online discussions. The author documents that bots affect the real people's views (Hjouji, 2018). The article raises concerns for future 2018 mid-term elections regarding how the bots are likely to affect the outcome thus newsworthy. The article result shows that a few numbers of active bots can significantly shift social network opinions (Hjouji, 2018). It's of importance to note that the article's analysis concentrated on the small number of users in comparison to the voters in the United States. The efforts of social media have not met a success yet on efforts to get rid of bots constantly tweeting to influence the voting population (Zaman, 2018).
References
Hjouji, Z. E., Hunter, D. S., Mesnards, N. G. D., " Zaman, T. (2018). The Impact of Bots on Opinions in Social Networks.arXiv preprint arXiv:1810.12398.
Zaman, T. (2018, November 05). Even a few bots can shift public opinion in ubig ways. Retrieved from https://theconversation.com/even-a-few-bots-can-shift-public-opinion-inbig-ways-104377
