Assignment On Giving Edge to Politics
Added on 2022-10-02
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Opinion Mining Through Tweets Giving Edge to Politics 2020 US Presidential Elections 1
Opinion Mining through Tweets Giving Edge to Politics of the 2020 US Presidential
Elections
By
(Name of Student)
(Institutional Affiliation)
(Professor’s Name)
(Date of Submission)
Opinion Mining through Tweets Giving Edge to Politics of the 2020 US Presidential
Elections
By
(Name of Student)
(Institutional Affiliation)
(Professor’s Name)
(Date of Submission)
![Assignment On Giving Edge to Politics_1](/_next/image/?url=https%3A%2F%2Fdesklib.com%2Fmedia%2Fimages%2Frn%2F4108c041e4144537bbf4897023425b46.jpg&w=3840&q=10)
Opinion Mining Through Tweets Giving Edge to Politics 2020 US Presidential Elections 2
Introduction
In the current world, social media is considered to have huge and an unprecedent amount
of opinionated data which one can deal with. Opinion mining is that branch of data analysis that
deals with the analysis of a person’s opinions and emotions related with particular services,
trending matters, associated organizations and events in general (Bo Yuan, 2016). Microblogging
site such as Twitter have become a huge mine of information on different topics of interest
(Meduru et al., 2017). People always tweet over latest happenings with a “hashtag” which is
considered as the fundamental topic for the examination. The data is usually collected by use of
the streaming API of Twitter (Gebrekirstos, 2011). This work represents the analysis of the
tweets through the use of opinion mining to predict the 2020 US presidential election. The tweets
from US citizens from five major states were selected for the analysis and the results discussed.
Research Methodology
The opinion mining by the use of Twitter Feeds assists in understanding the responses of the
masses in relation to the administrative matters and political transformations (Rao &
Ravichandran, 2018).
i. Data Collection
The data for this study was collected through streaming API of the Twitter as tweets that were
live were given top consideration.
ii. The Text Pre Processing
This refers to the process of clean up and preparation of the dataset for evaluation of the value of
the opinions and sentiments (Bo Yuan, 2016). The preparation of the dataset was done in such
ways such as removal of special characters, removal of URLs and Emojis and through removal
of slangs.
Introduction
In the current world, social media is considered to have huge and an unprecedent amount
of opinionated data which one can deal with. Opinion mining is that branch of data analysis that
deals with the analysis of a person’s opinions and emotions related with particular services,
trending matters, associated organizations and events in general (Bo Yuan, 2016). Microblogging
site such as Twitter have become a huge mine of information on different topics of interest
(Meduru et al., 2017). People always tweet over latest happenings with a “hashtag” which is
considered as the fundamental topic for the examination. The data is usually collected by use of
the streaming API of Twitter (Gebrekirstos, 2011). This work represents the analysis of the
tweets through the use of opinion mining to predict the 2020 US presidential election. The tweets
from US citizens from five major states were selected for the analysis and the results discussed.
Research Methodology
The opinion mining by the use of Twitter Feeds assists in understanding the responses of the
masses in relation to the administrative matters and political transformations (Rao &
Ravichandran, 2018).
i. Data Collection
The data for this study was collected through streaming API of the Twitter as tweets that were
live were given top consideration.
ii. The Text Pre Processing
This refers to the process of clean up and preparation of the dataset for evaluation of the value of
the opinions and sentiments (Bo Yuan, 2016). The preparation of the dataset was done in such
ways such as removal of special characters, removal of URLs and Emojis and through removal
of slangs.
![Assignment On Giving Edge to Politics_2](/_next/image/?url=https%3A%2F%2Fdesklib.com%2Fmedia%2Fimages%2Fpi%2F79b359520b11456ea1767b6ebfb463c1.jpg&w=3840&q=10)
Opinion Mining Through Tweets Giving Edge to Politics 2020 US Presidential Elections 3
iii. Analysis of the Sentiments
After refining of the data, the next step was to measure the opinion and the sentiments of the
tweets as either positive, negative or neutral. The positive sentiments according to the data
refinement refers to an opinion that Donald Trump would be elected as the president of the US in
2020. Negative sentiment on the other hand referred to the opinion that Trump will not be
elected as the president in the forthcoming election. The undecided citizens’ tweets were
classified as neutral opinions.
iv. Sampling Methods
The analysis is based on the dataset of about 30 million tweets that were collected over a period
of two months which are composed of the hashtags concerning the forthcoming 2020 politics and
election in the United States. The selected tweets from different parts of the US were selected for
the analysis. The tweets were further categorized according to the location of the tweeters and
the contents of the filtered and useful tweets.
Research Questions
For this study, the following research questions can be formulated;
i. Can opinion mining through tweets give an edge to politics of 2020 US presidential
elections?
ii. Can Donald Trump be re-elected in 2020 as the president of the United States?
Findings and Analysis
The results based on the analysis allows us to draw some opinions and predictions
relating to the forthcoming general election in the US. By analyzing the political conversation
data, the graphs below show the responses of the tweeters to the hashtag “Trump”. The pie charts
below represent the integration of the mass opinions from the major states along with the
iii. Analysis of the Sentiments
After refining of the data, the next step was to measure the opinion and the sentiments of the
tweets as either positive, negative or neutral. The positive sentiments according to the data
refinement refers to an opinion that Donald Trump would be elected as the president of the US in
2020. Negative sentiment on the other hand referred to the opinion that Trump will not be
elected as the president in the forthcoming election. The undecided citizens’ tweets were
classified as neutral opinions.
iv. Sampling Methods
The analysis is based on the dataset of about 30 million tweets that were collected over a period
of two months which are composed of the hashtags concerning the forthcoming 2020 politics and
election in the United States. The selected tweets from different parts of the US were selected for
the analysis. The tweets were further categorized according to the location of the tweeters and
the contents of the filtered and useful tweets.
Research Questions
For this study, the following research questions can be formulated;
i. Can opinion mining through tweets give an edge to politics of 2020 US presidential
elections?
ii. Can Donald Trump be re-elected in 2020 as the president of the United States?
Findings and Analysis
The results based on the analysis allows us to draw some opinions and predictions
relating to the forthcoming general election in the US. By analyzing the political conversation
data, the graphs below show the responses of the tweeters to the hashtag “Trump”. The pie charts
below represent the integration of the mass opinions from the major states along with the
![Assignment On Giving Edge to Politics_3](/_next/image/?url=https%3A%2F%2Fdesklib.com%2Fmedia%2Fimages%2Foh%2F80afb136a6ff4c2597cabfc5b0bedfca.jpg&w=3840&q=10)
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