Washington Post Comments Cluster Analysis

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WASHINGTON POST COMMENTS CLUSTER ANALYSIS
By (Name)
The Name of the Class (Course)
Professor (Tutor)
The Name of the School (University)
The City and State where it is located
The Date

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Washington Post Comments Cluster Analysis
Introduction
With the ongoing social media migration it is only natural that a significant percentage of
daily communication is prescribed over social networking platforms like Skype, Facebook,
Instagram, Snapchat, and Twitter. A major advantage of social media utility is that online
connectivity allows for people from diverse socio-economic and political backgrounds to
effectively communicate their opinions/views on a given product, event, or topic (Alexandra
2015). Tertiary learning institutions believe that social media utilization can to a large extent
improve the communication skills of students; since, they are provided with a platform to freely
express themselves. Online communication has bridged the divide between real-time event
reporting and ease access to reliable information. Online social media News pages like the New
York Times and Washington Post are popular because the report important issues that are vital to
the population in a timely manner (Alexandra 2015).
Traditional print materials such as newspapers, tabloids, and magazines are faulted for
reporting issues hours or even days after they happen. Moreover, most of these print materials
are not considered readily accessible by thousands of News consumers. In the current age, social
networking has become an important aspect of everyday live (Bertot, Jaeger & al. 2012). As
such, useful and diverse information can be accessed and retrieved from social media platforms
that can be used to draw inferences on the opinions and well-being of the entire population. It is
not uncommon to find businesses sing social media feedback and opinions to better their
products and overall service delivery (Osterrieder 2013). However, due to the presence of large
quantities of nonsensical information, and general perception that social networking is a time
wastage endeavor; many scientists have refused to comprehensively study its overall application

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the resolution of social and economic issues. Other issues that plague social media include:
copyright and legal issues, online bullying, and violation of privacy. Nevertheless, social media
is a powerful data source for scientist when used appropriately (Kaplan & Haenlein 2010).
Objectives
Overview and Implication of Selected Posts
The first one hundred comments we retrieved from a post on the Facebook page of the
Washington Post that focuses on the promise of tax-cuts for middle-class Americans in
November made by President Donald Trump. The question on most people's mind is who are
considered as middle-class income earners in the United States of America (Burman 2014).
According to researchers, adjusting for inflation the mean income of full-time employees has
changed by a very small margin over the past four decades. The average worker in a State like
Washington has witnessed the following change in annual income level (without adjustment for
inflation): 1974-$42,000 and 2013-$50,000. Most workers feel that the wage rate should have
more than doubled in 2018 since the 1970s; such that middle-class individuals take home
$92,000 per year before taxes. This assumption is supported by the fact that the cost of living has
increased substantially and so too have labor market requirement (e.g. A college degree for an
entry-level job) (NEC & Staff 2012).
Economists do not support the President Trump's plan to reduce taxes for middle-class
Americans especially in the wake of the prevailing debt crisis. First of all economist predict that
cutting taxes for the middle-class earners will reduce real consumer spending by 1.9 percentage.
This figure may not sound like a lot, but considering the government will be issuing billions in
tax cuts; the resulting reduction in spending will be in terms of millions or even billions (Burman
2012). This reduced spending will more than negatively affect the country's domestic industries

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and markets. Secondly, economists fear that the government will run out of funds to conduct
important activities and incentives. As such, money will be redirected from some incentives like
Medicaid and Social Security to more crucial activities like military advancement. Moreover, the
US government will be forced to borrow from other countries like China to offset any gaps in the
national budget (Nallareddy, Rouen & Serrato 2018).
The Second post is centered on the issue of same-sex relationships. It details the story of
two individuals named Harold who fell in love during a time period when being a member of the
LGBTQ was seriously discouraged. Religious condemnation of same-sex relationship has been
championed in the USA since the 1800s (Golden 2017). Laws were put in place to discourage
same sex attraction amongst men they were referred to as sodomy laws. Majority of the
executions and imprisonments carried out during this period were enforced under these laws.
Prior to the 18th century homosexuality was largely unenforced, because a significant population
of people in influential and administrative positions were known to partake in same-sex
fornication. In the late 20th century, significant movement emerged that championed for LGBTQ
rights in the USA after cruel and inhuman treatment was witnessed across of gay individuals.
Moreover, the medical procedures devised in the last 1950s to turn homosexuals into
heterosexuals were founds to be ineffective, and crude. They ranged from simple oral medication
to routine shock therapy; allow of which were found to have very low success outcome (Golden
2017).
In spite of the legalization of LGBT rights in the United States of America, many
individuals are still treatment with hostility and denied access to given amenities, For instance,
the USA laws do not protect the employment rights of LGBT members in over 25 States. As
such, an individual can be barred from an employment opportunity or fired from a job based on

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their sexual preferences (Pacheco 2010). As such, a gay individual will have limited job
opportunities in the labor market compared to a heterosexual person with the same qualification.
One of the most controversial areas for LGBT individual to get employment is in the US army.
With increments in the number of people affected directly or indirectly by LGBT issues,
government agencies have come under fire to amend the recruitment requirements in the US
army. Moreover, Labor unions sensitive to the employment issues faced by LGBT members are
pushing for workplace rules and ethics that will make employers more sympathetic and
accommodating. In spite of all these, online platforms have shown to be the most difficult to
control in terms of the way people approach homosexuality (Willett 2008). Social media
platforms are notorious for being used to bully and stigmatize members of the LGBT
communities; As such, parents and NGOs have called for regulation and monitoring of social
media platforms like Twitter and Facebook to prevent undue harassment and torment of gay
adolescents (Pacheco 2010).
Main Analysis Objectives
The main objective in this assessment is to establish comment segments in the two
Facebook posts. By so doing, the researcher will be able to assess the effectiveness in
communication of current issues across social media platforms. This investigation will focus
exclusively on News items posted by the Washington Post on their Facebook page. By analysis
this data we will be able to tell with some level of confidence the degree to which people
understand and interpret News stories (Baruah 2012). Misrepresentation and Alteration of
information by News channels will after the manner in which information is received and
internalized by readers; especially if the readers have a more accurate understanding o the
matter. For instance, a small number of the comments in the "middle-class tax-cut" post are

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faulting the Washington Post for broadcasting misleading information that is unlikely to take
place due to the fact that congress is currently on recess. There are several other objectives that
stem from each of the nine coding parameter. For instance, we will assess the degree with which
Americans criticize the current government with regard to their policy making ability, tax-
reductions, and debt crisis resolution.
Another important objective is to investigate the intensity and seriousness employed by
social media users when it comes to social, political, environmental, religious, and economic
issues. This objective will provide clarity on how much of the data collected from social media
platforms is actually useful in opinion, review, and feedback collection. This information will
allow us to place a dependability/reliability percentage on social media data; instead of
generalizing and stating that social media data is largely nonsensical. Since, we will be
investigating a political issue (tax-cut post) and a social issue (elderly gay couple) we have to
limit our population inferences to these two areas.
Therefore the research question is:
1. What homogenous clusters of comments emerged from the responses of people on two
Facebook stories posted by the Washington Post?
Method
A cluster analysis will be utilized using SPSS statistical software. The data will be
presented a categorical, because for each of the nine variables the data takes on a specific value
from 1 to 7 with 1 being the "most ideal" and 7 being the "least ideal". Since the order of the
values allotted/assigned is important the nine coding parameters will be presented in SPSS as
ordinal variables. A cluster analysis also referred to as taxonomy or segmentation analysis is an
exploratory assessment that is meant to divulge structures within the data. The specific purpose

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of the taxonomy analysis is to identity and highlight homogenous groups (especially if this
information was unknown during the grouping process) (Lani 2009). Due to the exploratory
nature of a segmentation analysis the process does not provide a differentiation between the
explanatory and response variables. The usefulness of the information provided by the cluster
analysis is to a large extent dependent on the researcher's ability to interpret the results. Some
researchers normally choose to accompany the cluster analysis with a discriminant analysis, as a
means of better understanding the results (i.e. SPSS outputs) (Lani 2009).
The intension in our cluster analysis is the opposite of what we seek to accomplish in
factor analysis. In cluster analysis the researcher attempts to group together cases or people;
while, in factor analysis we try to group together variables. As such, the manner in which people
respond to the Washington' posts will be used as a basis for allocating individuals to given
clusters (Field 2017). The grouping of the individuals will be based on the similarities in their
responses. In the chart below we can group Michael and Andrew in the same group but Leo will
be in another group of his own; therefore, we will have two cluster groups. Therefore in the
formulation of cluster segments we will try to look at individuals with similar responses across
all nine variables. In our case, a graph is not the best solution because we will have 400
individuals and each of their responses have been ranked according to nine variables/parameters.
Therefore, a more suitable measure of similarity has to be used; for instance, coefficients of
similarity and dissimilarity (Field 2017). In SPSS we will employ the use of the Euclidean
Distance which measures/surveys the distance between two individuals/cases. In this analysis we
will not explore for similarities across variables, because this is not required under the research
objectives. The results of the SPSS cluster analysis will be attached below for interpretation

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while the more comprehensive charts and tables will be added to the appendix for referencing
(Field 2017).
Limitations
In spite of the numerous benefits associated with cluster analysis there are however some
drawbacks that can be sited. For instance, the different cluster analysis techniques yield different
results (Field 2017). As such, one researcher may yield a favorable result using one techniques
and another researcher gets a discouraging report from another cluster analysis methodology.
This takes places due to the variation in the criteria used to develop clusters. Therefore, each
cluster technique has to be selected keenly to best suit the desired research objective. Secondly,
the results of a cluster analysis will also be affected by the ordering technique employed in the
variables; excepting simple linkage (Field 2017). Thirdly, taxonomy analysis tends to loss
stability when cases are dropped from a give cluster. This is because a cluster analysis is highly