Please upload a plain .txt file with the text you would like to analyze.


Downaload Sample Text

Windows Users: Please use a .txt plain text file extension via NOTEPAD *.

Linux Users: Please use a .txt plain text file extension.

Mac Users: Please use a .txt plain text file extension via TEXTEDIT *.

Plain text tutorial: Windows and Mac

* Please ensure the file uploaded utilizes UTF-8 encoding
This tab displays the uploaded text file.

Text Ouput

This tab allows you to display the frequency of words in the uploaded text
via a bar chart. The bar chart by default displays the first through tenth
most frequent words in the text.
Download Barplot
The minimum frequency refers to the minimum number of times
the word needs to appear in the uploaded text to be included in the wordcloud.
The maximum number of words refers to the maximum number of words
you want to appear in the wordcloud that is created.
Download Wordcloud
This tab allows you to calculate eight types of emotion present within the uploaded text.

The following types of emotion are calculated:

Anger, Anticipation, Disgust, Fear, Joy, Sadness, Surprise, and Trust.
The emotions calculated are the 8 basic universal emotions conveyed by humans in all cultures.
Each bar represents the overall percentage of each emotion present within the uploaded text file.


Download Emotional Sentiment Barplot
This tab allows you to calculate the positive and negative sentiment present within the uploaded text.

The following sentiments are calculated:

Positive & Negative
The bar graphs displayed are in relation to the percentage of positive and negative words present in the uploaded text.


Download Pos vs. Neg Barplot

The data table created calculates the percentage of each emotion present within the uploaded text file and outputs it to a table.

The following emotions are calculated:
Anger, Anticipation, Disgust, Fear, Joy, Sadness, Surprise, and Trust.

The emotions calculated are the 8 basic universal emotions conveyed by humans in all cultures.

Reference: NRC Package




Download Emotional %
This tab allows you to plot the trajectory of the uploaded text.

The plot will display the overall emotion of pieces of the text at different successive linear locations in the text. Large text files will be more condensed than small text files.
The plot displayed can be thought of as the story arc in a movie or book. If text items besides books are used it is highly suggested to order the text correctly. The graph will show
how the emotional content of the uploaded text has changed over time e.g. beginning of a text to the end of the text.The Narrative Timeline axis refers to how the book,text, or comments
have changed from the beginning of the text to the end of the same text being analyzed. The Emotional Valence axis refers to the positive/good-ness and the negative/bad-ness of the text.
Positive valence or upward motion can be seen as the good linear parts of a story, while Negative Valence can be thought of as bad or negative linear parts of the story. Therefore,
as the plotted line moves up or down it is in turn visualizing the good or bad parts of the text being analyzed.


Download Plot Trajectory
This tab allows you to create a bar chart that displays both the type of emotion and type of sentiment
present within the uploaded text file. The percentage of each emotion and sentiment is displayed at
the top of each bar.


This tab allows you to utilize a word tokenizer to see which words in a text are displayed together.
You can choose to display words from 1 to 5 tokens. Therefore, words that appear next to each other
in the uploaded text will be displayed. If you choose 2, then two words that appear next to each
other will be displayed. You can choose up to 5 words that display next to each other, thus allowing
you ,the end user, to look for patterns in any text.
This tab allows you to display sentences by emotion. A sentence may appear more
than once if an one emotion is closely related to another: e.g. anger and disgust.


Download Sentence Breakdown
Select the following number below that corresponds with the emotion you want to display:

1 = Anger 2 = Anticipation 3 = disgust 4 = Fear 5 = Joy

6 = Sadness 7 = Surprise 8 = Trust 9 = Negative 10 = Positive


This tab allows you to display the frequency of each word present within the uploaded text file.
The frequency of each word will be shown and can be searched via the interactive table displayed below.


Download Word Breakdown
References :

Cashell, D. (2014). Social media sentiment analysis using data mining techniques . National College of Ireland.

Hennessey, A. (2014). Sentiment analysis of twitter: using knowledge based and machine learning techniques . National College of Ireland.

Jockers, M. (2016). Introduction to the syuzhet package .Retrieved from: https://cran.r-project.org/web/packages/syuzhet/vignettes/syuzhet-vignette.html

Mohammad, S. (2013). NRC word-emotion association lexicon (aka emolex) .Retrieved from: http://saifmohammad.com/WebPages/NRC-Emotion-Lexicon.htm

Mullen. (2014). Introduction to sentiment analysis .Retrieved from: https://lct-master.org/files/MullenSentimentCourseSlides.pdf

Robinson, D. (2016). Text analysis of trump's tweets confirms he writes only the angrier android half .Retrieved from: http://varianceexplained.org/r/trump-tweets/

Smith, D. (2015). Comparing subreddits, with latent semantic analysis in r . Retrieved from: http://blog.revolutionanalytics.com/2017/03/comparing-subreddits.html
Application Author: Ben Gonzalez

Email: gonzalezben81@gmail.com

Phone: 314-472-5417
Build your own Linux Server and host your own app with a $10 credit on Digital Ocean

Click on this link to get your Digital Ocean Credit: Digital Ocean $10 Credit