Task Solutions-Human and data ethics in Twitter research: IT590

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CASE STUDY ANALYSIS- Wheeler, J. (2018). Mining the first 100 days: Human and
data ethics in Twitter research. Journal of Librarianship & Scholarly Communications, Special
Issue, 6, 1–23
Your Name
Department of ABC, University of Wisconsin –Whitewater
ABC 101: Course Name
Professor (or Dr.) Firstname Lastname
Date
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Abstract
The report is acase analysis of “Mining the first 100 days: Human and data ethics in
Twitter research. Journal of Librarianship & Scholarly Communications”. Here the ethics of data
collection is discussed broadly. The analysis of the case study suggests that there is much scope
for improvement. The research outcomes suggest that there API of Twitter is not good for
carrying out the research. The data ethic has to be given due significance. Users, as well as the
social media platforms, are equally responsible for their data integrity and ethics.
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Table of Contents
Introduction or Background …………………………………………………………………………………… 4
Major Issues ………………………………………………………………………………………………………… 4
Alternative Courses of Action ………………………………………………………………………………… 6
Recommendation ………………………………………………………………………………………………….. 7
Conclusion …………………………………………………………………………………………………………… 7
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CASE STUDY ANALYSIS- Wheeler, J. (2018). Mining the first 100 days: Human and
data ethics in Twitter research. Journal of Librarianship & Scholarly Communications, Special
Issue, 6, 1–23
Introduction or Background
The U.S presidential elections of the year 2016 were an example of how people can be
manipulated or data be misinterpreted in this digital age. The case to be analyzed is related to
what the users of Twitter “heard” and the way they replied to the use of #MAGA Make America
Great Again in the initial 100 days of the new management. The report will provide aproper
analysis of the case study. There is aneed to understand if social media has distorted the
boundaries existing amid producers of information and customers. Here the statement that
“social media has blurred the boundaries existing between producers of information and
customers” is supported. The analysis was done that will be done will be surrounding this
statement. The sections are major issues, alternative courses of action, recommendations, and
lastly conclusion.
Major Issues
The major issues from the case study are surrounding the excessive influence of social
media on the decision-making power of individuals. The social media platform that will be
discussed highly is Twitter. The dynamics, as well as the impact of fake news on Twitter in the
2016 US Presidential election, are yet to be clarified. “Fake news” being mentioned here refers to
fabricated information that is disseminated as deceptive content (Bovet & Makse, 2019) .
Misinformation and out-of-the-box propaganda are not new but then their significance has
certainly increased in this social media age. Massive digital misinformation is already termed a
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prime technological and geopolitical risk by the World Economic Forum â€sreport of the year
2013 (Bovet & Makse, 2019) .It has to be agreed that online campaigning strategies have
become much more mature to keep up with the pace of evolving social media. With the growing
relevance of social media and smartphone usage approaching avalue of 60% or even exceeding
that, digital advertising in the year 2016 is way beyond the symbolic gesture that was in the prior
elections(Das Sarma, 2022). Here itcan also be said that Twitter has remarkably high
dissemination of content. In this context, the researcher suggests that if atweet is retweeted once
then there are high chances of itgetting retweeted to 4levels of separation from the producer of
the content (Das Sarma, 2022). Thus, in all ways, users of Twitter can be said to be bombarded
by events that are politically motivated even if these do not directly follow the creators of the
political content. This is ahuge concern as negative word of mouth spreads faster and can be said
to be far more effective as compared to positive word of mouth. In these times of Presidential
elections, Twitter was overflooded by political tweets that were again loaded with negativity.
This is evidence enough that oversaturation of politics in any specific medium can lead to
extreme situations that of political aversion.
Original content produced on the platform Twitter by the private citizens, the majority of
the time takes the conversational form of word of mouth communication and this is something
much different from the various other forms of social media. Controversial arguments that spread
false facts related to election results are something concerning society. Thus, the major issue is
the spread of the word influencing people’s thoughts and behaviors negatively.
Consent is yet another feature of SMR in which the conventions made were reliant on the
past practices and these were also subjected to assessments of background and intent of the user
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Social media platform such as Twitter constrict auser â€santicipation of privacy and creates
consensus for unplanned use of their civic content.
Data collection using the API of Twitter comes up with multiple issues such as the API
constraints in place being ahindrance on the path of the researcher. Frequently changing
business models of Twitter need to be addressed. There is abrupt discontinuation of whitelisting
and then again newly imposed limitations regarding API.
Alternative Courses of Action
The alternative course of action in the context of this is that people should be made aware
of how social media is being used to twist and turn information. Social media platforms cannot
be trusted blindly. It is afact that when signing up for anew account on social media platforms
the users are the ones to provide the details and accept the disclaimer message agreeing to the
terms and conditions. The users are not much bothered about the data they are agreeing to be
shared with the social media platforms. It is also the responsibility of the users to check for the
authenticity of the news or go on to check for the sources before jumping to aconclusion or
retweeting the tweet.
Apart from this, modern methods such as decision trees, support vector machine and
lastly logistic regression algorithms can be made use of to detect fake accounts on Twitter.
Classification performance of the above-mentioned methods is compared and the related logistic
regression showed to be more appropriate as compared to others. The location of the tweets
using the data of geo location if enabled on the Twitter account can be checked. All in all, the
alternative actions hint at the fact that the users need to be more particular about the permission
that they are giving to the social media platforms and the way these data will be used. The
increasing dependence on the modern day media is to be increased rather than focusing on the
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new sites such as Twitter and social media networking sites. Business models of social media
platforms have got altered over the time to meet the requirements and associated expectations of
the users and the ones who are the advertisers on the platform (Ahmed, 2021). Privacy of data on
Twitter is amixed responsibility of both the social media platform and the users. The concern is
about the susceptible populations within the platform of Twitter. Some privacy leaks affect the
users to agreat extent and can lead to serious consequences.
Recommendation
The recommendation that needs to be proceeded with is that modern methods
such as decision trees, support vector machine algorithms and others to be used. The
researcher when collecting data needs to understand the significance of the research.
They are the ones vested with the duty to come up with proper data that is authentic. Thus,
the modern methods to be used.
The process to be used for implementation are as follows:
1. Find out how these can be used in the research.
2. Experts need to be included in the research process
3. There has to be proper information provided about the use of data.
4. The rules and regulations that are to be in place to use these tools also require
focusing on.
Conclusion
The study thus suggests that social media platforms are to be attributed partial
responsibility for the data being shared and misinterpreted on their platforms. Here the author
tried using the API of Twitter to carry out the research work but faced different issues. The main
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issue is that the users are also responsible for the leakage of their data or the privacy issues that
happen. Data mining of the Twitter data or the usage of the data is something that cannot be
viewed to be aproper thing. In the process, the users do not get to understand the extent to which
their data is breached. They can be said to be alay man in the context requiring much
information otherwise.
SWOT analysis of the case study
S There is proper structuring done in the case
study. The literature review has been divided
into different sections. Use of proper
statistics.
W There is much information and fewer citations
used. Twitter data has to be evaluated in terms
of different aspects and this has to be
checked.
O There is much scope to include acomparison
of the features of Twitter in the initial days
and of the features during the present times.
T Many such studies are on similar topics. The
credibility of the research is questionable as
the author has included much of his views and
perceptions. The case analysis also hinted at
the fact that
SWOT table
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(Source: created by author)
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References
Ahmed, W. (2021). Using Twitter as adata source for an overview of social media
research tools (2021). Impact of Social Sciences Blog .
Bovet, A., & Makse, H. A. (2019). Influence of fake news on Twitter during the 2016 US
presidential election. Nature communications ,10 (1), 1-14.
Das Sarma, M. (2022). Tweeting 2016: How Social Media is Shaping the Presidential
Election. Retrieved 10 May 2022, from http://www.inquiriesjournal.com/articles/1454/tweeting-
2016-how-social-media-is-shaping-the-presidential-election
Wheeler, J. (2018). Mining the first 100 days: Human and data ethics in Twitter
research. Journal of Librarianship and Scholarly Communication ,6(2).