Article Assignment 1 (2)
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School
University of Michigan, Flint *
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Course
215
Subject
Communications
Date
Apr 3, 2024
Type
Pages
4
Uploaded by CorporalBookAnt87
1.
Studying world leaders' use of social media platforms like Twitter during the COVID-19
pandemic
is
crucial
for
understanding
their
strategies
for
engaging
citizens,
disseminating
information,
and
shaping
public
opinion.
Accurate
and
timely
communication is essential during public health emergencies to inform, reassure,
mitigate misinformation, and encourage adherence.
2.
G7 Twitter Outcome Measures on March 18, 2020:
●
Verified Twitter accounts
●
Number of followers
●
Number of COVID-19 related viral tweets.
●
Categorized viral tweets into "Informative," "Morale-boosting," or "Political."
●
Weblinks in informative tweets to official government-based sources.
●
Top viral tweet characteristics for each G7 member.
●
Number of viral videos embedded in informative tweets.
●
Non-English language tweets and their translations.
3.
The variable "themes for viral tweets" was organized into three categories or attributes:
➔
Informative: Tweets providing information or updates related to COVID-19.
➔
Morale-boosting: Tweets aimed at boosting morale or galvanizing people during
the pandemic.
➔
Political: Tweets raising a point of political debate related to COVID-19.
The themes are distinct categories without any inherent order, so this variable is measured
nominally. The mode, the most frequent category in categorical data, is the best measure of
central tendency.
Each theme category's tweet percentages:
➔
Informative: 82.8%
➔
Morale-boosting: 9.4%
➔
Political: 6.9%
The majority of viral tweets were "Informative," 82.8%. This suggests that most G7 tweets
during the COVID-19 pandemic provided crisis updates.
4.
To analyze the variable from Table 1, we must determine the level of measurement,
which is an interval, as the number of followers is a continuous quantitative variable.
Let's calculate these values: 4.7, 4.6, 0.4, 1.7, 1.6, 71.4, 1.1, 0.2
Median = (1.7 + 1.6) / 2 = 1.65 million
Mean = (4.7 + 4.6 + 0.4 + 1.7 + 1.6 + 71.4 + 1.1 + 0.2) / 8 = 10.7125 million
Standard Deviation:
●
Variance = [
Σ
(xi - x
̄
)²] / n
●
Sum of squared differences
37.6216+37.5156+108.7321+73.9884+73.4584+3712.3184+81.4569+101.8696=4226.961
Variance=4226.961/8=528.3701
Standard Deviation=528.3701
≈
22.98
So, the standard deviation for the "Followers (million)" variable, given a variance of
528.3701 is approximately 22.98
million
a.
Discussion of Results:
The large standard deviation of approximately 22.98 million indicates a diverse set of
followers among G7 leaders, influenced primarily by Donald Trump's outlier status.
5.
Now, let's calculate the median, mean, and standard deviation for the "Informative" tweets:
Informative tweets: 61, 24, 8, 20, 16, 51, 2, 21
●
Median = (20 + 16) / 2 = 18
●
Mean = (61 + 24 + 8 + 20 + 16 + 51 + 2 + 21) / 8 = 25.375
Standard Deviation:
●
First, calculate the variance.
●
Variance = [
Σ
(xi - x
̄
)²] / n
Next, we'll calculate the squared differences from the mean for each data point:
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(61−25.375)2,(24−25.375)2,(8−25.375)2,(20−25.375)2,(16−25.375)2,(51−25.375)2,(2−25.375)2
,(21−25.375)2
=1416.515625+3.140625+299.890625+33.640625+92.015625+1062.890625+517.640625+18.6
40625=3444.375
Variance = 3444.375/8=430.547
Standard deviation = 430.547
≈
20.757
After calculations, the standard deviation for the "Informative" tweets variable is approximately
20.757
a.
The mean and median of "Informative" tweets from G7 world leaders show a right skew,
with a slightly higher mean (25.375) and a standard deviation of 20.757, indicating some
variation in the number of informative tweets.
6
. The study found that G7 leaders tweeted informative, morale-boosting, and political
messages during the pandemic. Morale-boosting tweets provided emotional support, while
informative tweets provided accurate information. Political tweets may have influenced public
discourse. Effective communication, public perception and behavior, and policy decisions
depend
on
leaders'
Twitter
use
during
crises.
Analyzing
leaders'
tweets
can
improve
communication, trust, and public health crisis response
.