This article provides a discussion of different tools that can be used to perform research on Twitter. The study then utilizes sentiment analysis to demonstrate self-sentiment of the POTUS and compare it with popular news sources. A comparison in 2 time periods and 4 months apart was made to determine if there is a change in the self-sentiment of the POTUS versus common news sources. To perform sentiment analysis, we utilize Python and the Vader and Pandas libraries, and statistical analysis was performed for each of the datasets. The first round of tests were based on a November dataset and revealed the means between the public, FOX, CNN and the President were not equal and that the POTUS had a higher self-sentiment than the sentiment of t...
Sentiment Analysis is an actively growing field with demand in both scientific and industrial sector...
Sentiment analysis, also known as opinion mining, is an application of natural language processing (...
In this thesis, the author examines the last 131 days of the 2016 election cycle. This analysis focu...
With the increasing level of access to online political discourses, made possibleby the social media...
In our project, tweets are collected using the Twitter streaming API from Twitter. The collected twe...
We used computational tools to explore president Donald Trump's tweeting habits and some of the effe...
Twitter, as one of the popular social networks today and big data generator, can affect and change t...
This paper reports on an evaluation of five commonly used, lexicon-based sentiment analysis tools (M...
This research focuses on the language tone of the United State of America’s presidentrelated ...
The user base for social media platforms have seen sharp increases in nearly every year since their ...
In the age of social media, everyone has the ability to post their thoughts and feelings about sever...
The correlation between Twitter sentiments and polling results for the 2016 presidential race / Dev...
Emotion mining is becoming an important part of the sentiment analysis. Online text sources are evol...
Sentiment analysis deals with identifying and understanding opinions and sentiments expressed in a p...
Perhaps analogous to President Franklin D. Roosevelts use of radio for his fireside chats, President...
Sentiment Analysis is an actively growing field with demand in both scientific and industrial sector...
Sentiment analysis, also known as opinion mining, is an application of natural language processing (...
In this thesis, the author examines the last 131 days of the 2016 election cycle. This analysis focu...
With the increasing level of access to online political discourses, made possibleby the social media...
In our project, tweets are collected using the Twitter streaming API from Twitter. The collected twe...
We used computational tools to explore president Donald Trump's tweeting habits and some of the effe...
Twitter, as one of the popular social networks today and big data generator, can affect and change t...
This paper reports on an evaluation of five commonly used, lexicon-based sentiment analysis tools (M...
This research focuses on the language tone of the United State of America’s presidentrelated ...
The user base for social media platforms have seen sharp increases in nearly every year since their ...
In the age of social media, everyone has the ability to post their thoughts and feelings about sever...
The correlation between Twitter sentiments and polling results for the 2016 presidential race / Dev...
Emotion mining is becoming an important part of the sentiment analysis. Online text sources are evol...
Sentiment analysis deals with identifying and understanding opinions and sentiments expressed in a p...
Perhaps analogous to President Franklin D. Roosevelts use of radio for his fireside chats, President...
Sentiment Analysis is an actively growing field with demand in both scientific and industrial sector...
Sentiment analysis, also known as opinion mining, is an application of natural language processing (...
In this thesis, the author examines the last 131 days of the 2016 election cycle. This analysis focu...