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Commit 9fe11a58 authored by Maggie Kocorowski's avatar Maggie Kocorowski
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a bunch of changes

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......@@ -82,4 +82,3 @@ footer {
color: #fff;
padding: 20px 0;
}
......@@ -26,6 +26,12 @@
<section>
<h2>About Us</h2>
<ul>
<li><p>As first year students, this was our first codefest/hackathon!</p></li>
<li><p>we don't have much experience working with AI systems or coding languages outside of python</p></li>
<li><p>originally we brainstormed several ideas and attmpted to follow tutorials, but decided to work on pseudo code and research instead</p></li>
<li><p>learned how to work with new teammates, create new git project and connect to VS code, how VS code works, webpage setup and styling, etc.</p></li>
</ul>
<section class="main">
<section class="developers">
<div class="developer">
......@@ -35,6 +41,7 @@
<div class="description">
<h2>Christy Tran</h2>
<p>Developer</p>
<p>Computer Science</p>
<p>ctt57@drexel.edu</p>
</div>
</div>
......@@ -46,6 +53,7 @@
<div class="description">
<h2>Andersen Hu</h2>
<p>Researcher</p>
<p>Computer Science</p>
<p>ah3779@drexel.edu</p>
</div>
</div>
......@@ -57,17 +65,19 @@
<div class="description">
<h2>Maggie Kocorowski</h2>
<p>Front End Designer</p>
<p>User Experience and Interaction Design</p>
<p>mjk488@drexel.edu</p>
</div>
</div>
<div class="developer">
<div class="circular-image">
<img src="./ivy_headshot.jpg" alt="Ivy headshot">
<img src="./christy_headshot.jpg" alt="Ivy headshot">
</div>
<div class="description">
<h2>Ivy Shao</h2>
<p>AI Trainer</p>
<p>Data Science</p>
<p>is485@drexel.edu</p>
</div>
</div>
......@@ -75,9 +85,20 @@
</section>
</section>
<section>
<h2>What We Learned</h2>
<ul>
<li><p>Work with new teammates</p></li>
<li><p>Create a new project and add members in Git</p></li>
<li><p>How to conncet project to VS Code</p></li>
<li><p>How to use VS Code</p></li>
<li><p>learned how to work with new teammates, create new git project and connect to VS code, how VS code works, webpage setup and styling, etc.</p></li>
</ul>
</section>
<section>
<h2>Contact</h2>
<p>You can reach us at mjk488@drexel.edu</p>
<p>You can reach us at mjk488@drexel.edu.</p>
</section>
</main>
......
#Mission: Create a sentiment analysis extention that will take the users text and determine whether or not it is inclusive.
Depending on the users inclusivity it will display an approving/disapproving image.
#
Steps:
Research Sentimental Analysis
-Textblob
Create a Sentimental analysis program using Python
#
Research articles, hatespeech, etc... to use to train AI to determine what will be considered inclusive and exclusive.
Use Libaray to train AI
#
#
Pseudocode
Ask user for input (text from file/article/active typing)
Import libraries (TextBlob)
Libary (TextBlob) has API for tagging certain phrases
Check whether or not the text includes tagged phrase
If text includes tagged phrase, decrease the score
If text includes no tagged phrases, increase the score
Calculate the overall score of the user (difference)
If score is positive then display image of happy cat
If score is negitive then display image of angry cat
If score is neutral (zero) then display image of middle cat
from textblob import TextBlob
from newspaper import Article
url = "FIXME"
article = Article(url)
article.download()
article.parse()
article.nlp()
text = article.summary
print(text)
blob = TextBlob(text)
sentiment = blob.sentiment.polarity_# -1 to 1
print(sentiment)
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