Harshit iamharshit

Get Tweet Post Stock

An Android app that uses Machine Learning to correlate tweet sentiment and stock prices.

Overview

The project searches the Twitter API for tweets about a given company that a user wants to be monitored, and uses sentiment analysis to identify general sentiment about the company. Using the general time of those tweets, it would then find the change in stock market price for the company after a short delay to allow for those changes, and note whether the stock increased or decreased. This data was then fed into a machine-learning algorithm in order to predict whether a stock would rise or fall, given a general sentiment from tweets.

Dependencies

Twitter4J for getting access to tweets about the companies

	prompt = f"""
	Your task is to determine if the student's solution \
	is correct or not.
	To solve the problem do the following:
	- First, work out your own solution to the problem.
	- Then compare your solution to the student's solution \
	and evaluate if the student's solution is correct or not.
	Don't decide if the student's solution is correct until
	you have done the problem yourself.

	function generate_data()
	if exist('data_harshit.csv', 'file') == 2
	delete data_harshit.csv;
	end
	x=[-1000:20:1000];
	y=f(x);
	ans=vertcat(x,y)';
	csvwrite('data_harshit.csv',['x','y']);
	dlmwrite('data_harshit.csv',ans,'delimiter',',','-append');

	echo `rm myfile2.txt`

	declare -i count
	count=0

	declare -i total
	total=0
	cat vocab_chat.txt \| while read p; do
	total=total+1
	if echo "$p" \| grep '*'; then

	import theano
	import theano.tensor as T
	from helper import activations
	from helper import misc,updates
	from scipy.stats import gaussian_kde
	from matplotlib import pyplot as plt
	from matplotlib.pyplot import *
	from helper import inits
	from helper.theano_utils import floatX, sharedX