feconroses

11 ms·

61.
by feconroses 10y ago
Hi HN! For creating Tarsier, we used Tweepy for extracing tweets using the Twitter Public API, we used MonkeyLearn for analyzing the tweets and finally used Plotly for creating the visualizations. You can see some of the insights we got by
62.
Show HN: Understanding the US Elections Through Twitter and Machine Learning(tarsier.monkeylearn.com)
3 points by feconroses 10y ago|1 comments
63.
Trump gets about 450k mentions on Twitter per day, while Clinton only gets 250k(tarsier.monkeylearn.com)
2 points by feconroses 10y ago|0 comments
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Real-time sentiment monitoring for Clinton and Trump(tarsier.monkeylearn.com)
3 points by feconroses 10y ago|0 comments
65.
Trump gets 200,000 more mentions per day than Clinton on Twitter(blog.monkeylearn.com)
2 points by feconroses 10y ago|0 comments
66.
Trump vs. Clinton: a machine learning analysis on Twitter mentions(blog.monkeylearn.com)
2 points by feconroses 10y ago|0 comments
67.
Donald Trump vs. Hillary Clinton: A Sentiment Analysis on Twitter Mentions(tarsier.monkeylearn.com)
1 points by feconroses 10y ago|0 comments
68.
by feconroses 10y ago
You can check out the tool here: http://tarsier.monkeylearn.com/
69.
Donald Trump vs. Hillary Clinton: A Sentiment Analysis on Twitter Mentions(blog.monkeylearn.com)
6 points by feconroses 10y ago|2 comments
70.
Know your followers with Machine Learning(blog.monkeylearn.com)
3 points by feconroses 10y ago|0 comments
71.
Know Your Twitter Followers with Machine Learning(blog.monkeylearn.com)
4 points by feconroses 10y ago|1 comments
72.
Know your followers with Machine Learning(blog.monkeylearn.com)
1 points by feconroses 10y ago|0 comments
73.
Training a sentiment analysis classifier using a web scraping visual tool(blog.monkeylearn.com)
1 points by feconroses 10y ago|0 comments
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by feconroses 10y ago
Thanks Maëlle Salmon for this awesome analysis!
75.
Analyzing #first7jobs tweets with MonkeyLearn and R(blog.monkeylearn.com)
1 points by feconroses 10y ago|1 comments
76.
Machine Learning over 1M hotel reviews(blog.monkeylearn.com)
145 points by feconroses 10y ago|41 comments
77.
Interesting insights from analyzing over a million hotel reviews(blog.monkeylearn.com)
1 points by feconroses 10y ago|0 comments
78.
Machine Learning over 1M hotel reviews finds interesting insights(blog.monkeylearn.com)
2 points by feconroses 10y ago|0 comments
79.
Building a Twitter Bot with PHP and Machine Learning(blog.monkeylearn.com)
3 points by feconroses 10y ago|0 comments
80.
The Divided Kingdom: a machine learning analysis on the Brexit result(blog.monkeylearn.com)
2 points by feconroses 10y ago|0 comments
81.
New Languages on MonkeyLearn and teams and analyzing data with Excel and CSV files(blog.monkeylearn.com)
2 points by feconroses 10y ago|0 comments
82.
What are they listening for? A look into Facebook's AI Engine(linkedin.com)
1 points by feconroses 10y ago|0 comments
83.
by feconroses 10y ago
Awesome post! And great example on how you can use Machine Learning to makes salespeople life easier! Have you tried MonkeyLearn? You can easily create machine learning models on the fly, have great tools to improve your models (like explor
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R package for text analysis with Monkeylearn(github.com)
3 points by feconroses 10y ago|0 comments
85.
Getting actionable insights from reviews using Machine Learning(blog.monkeylearn.com)
3 points by feconroses 10y ago|1 comments
86.
Natural language processing in R with Monkeylearn's modules(github.com)
2 points by feconroses 10y ago|0 comments
87.
A Gentle Guide to Machine Learning(blog.monkeylearn.com)
4 points by feconroses 10y ago|0 comments
88.
Creating a sentiment analysis model with Scrapy and MonkeyLearn(blog.monkeylearn.com)
1 points by feconroses 10y ago|0 comments
89.
MonkeyLearn integration with Scrapinghub(blog.monkeylearn.com)
1 points by feconroses 10y ago|0 comments
90.
Making it easier to build text classifiers on MonkeyLearn(blog.monkeylearn.com)
2 points by feconroses 11y ago|0 comments

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