Twitter Sentiment Analyseris a Python command line app that analyses tweets to check for sentiments and emotions.- It has the following features;
- Fetch tweets
- Analyze frequency of words used in the tweets
- Saves the tweets fetched into a json file for further analysis
- Integrates with Alchemy API to get;
* Doc Sentiment of the collected tweets, with results being either,
- Positive
- Negative * Emotional Sentiments from the collected, which is further analysed to;
- Disgust
- Anger
- Fear
- Joy
- Sadness
- version 3.XX
- This app's functionality depends on multiple Python packages including;
- ascii-graph - This package handles console graphs, representing data in a visual manner, it also adds rendering with color
- docopt - This is a powerful commandline library that lets a user enter commands and any number of parameters.
- tweepy - This package handles integration to the twitter API, letting a user fetch tweets among other functions.
- watson-developer-cloud - This package handles integration with the Alchemy API
- prettytable - This package helps in rendering data in a tabular form
- nltk - This package provides a list of all stop words which are used to remove all stop words in the collected tweets
- Navigate to a directory of choice on
terminal. - Clone this repository on that directory.
- Using SSH;
>`git clone git@github.com:GathuBoswell/bc-12-Twitter-Sentiment-Analysis.git`
- Using HTTP;
>`git clone https://github.com/GathuBoswell/bc-12-Twitter-Sentiment-Analysis`
- Navigate to the repo's folder on your computer
cd Twitter-Sentiment-Analysis/- Install the app's package dependencies. For best results, using a virtual environment is recommended.
pip install -r requirements- Setup Your API Aunthentication Keys for Both Alchemy and Twitter API
python api_setup.py- Running the command above will produce output that's similar to the sample below.
Enter the Alchemy Api Key: XXXXXXXXXXXXXXXXXXXXXXXXXXXX
Enter the tWitter consumer key: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
Enter the tWitter consumer Secret: XXXXXXXXXXXXXXXXXXXXXXXXXXX
Enter the tWitter access key: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
Enter the tWitter access Secret: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
-
Run the app
python twitter_cmd.py -i- Running the command above will produce output that's similar to the sample below.
_______ _ _ _ |__ __| (_) | | | | |_ ___| |_| |_ ___ _ __ | \ \ /\ / / | __| __/ _ \ '__| | |\ V V /| | |_| || __/ | |_| \_/\_/ |_|\__|\__\___|_| _____ _ _ _ / ____| | | (_) | | | (___ ___ _ __ | |_ _ _ __ ___ ___ _ __ | |_ \___ \ / _ \ '_ \| __| | '_ ` _ \ / _ \ '_ \| __| ____) | __/ | | | |_| | | | | | | __/ | | | |_ |_____/ \___|_| |_|\__|_|_| |_| |_|\___|_| |_|\__| _ /\ | | / \ _ __ __ _| |_ _ _______ _ __ / /\ \ | '_ \ / _` | | | | |_ / _ \ '__| / ____ \| | | | (_| | | |_| |/ / __/ | /_/ \_\_| |_|\__,_|_|\__, /___\___|_| __/ | |___/ The list of commands available are as below =========================================== commands Description ----------------- ------------------- fetch <twitter_handle> <number_of_days_to_get_tweets_from> Get all tweets of the entered username wordfrequency Prints word count for all words in the tweets sentiment <--all> <--docsentiment> <--emotion> Prints sentiment analysis with specified option help prints the docopt menu of commands home prints this menu Twitter Sentiment Analysis Type help to view list of commands Twitter_Sentiment:> fetch @realdonaldTrump 7 100%|##########################################################################################################################################################| 5/5 [00:05<00:00, 1.17s/it] Twitter_Sentiment:> wordfrequency +-----------+-------+---------+ | Word | Count | Percent | +-----------+-------+---------+ | I | 46 | 3.16 | | The | 23 | 1.58 | | great | 16 | 1.10 | | win | 13 | 0.89 | | We | 13 | 0.89 | | time | 11 | 0.76 | | Trump | 10 | 0.69 | | Very | 10 | 0.69 | | GREAT | 9 | 0.62 | | election | 9 | 0.62 | | vote | 9 | 0.62 | | last | 8 | 0.55 | | President | 8 | 0.55 | | New | 8 | 0.55 | | people | 8 | 0.55 | | many | 8 | 0.55 | | night | 7 | 0.48 | | today | 7 | 0.48 | | Just | 7 | 0.48 | +-----------+-------+---------+ Twitter_Sentiment:> Twitter_Sentiment:> sentiment --all +----------------+----------+----------+ | Sentiment Type | Score | if_mixed | +----------------+----------+----------+ | positive | 0.969859 | 1 | +----------------+----------+----------+ Emotions Graph ############################################################################### █ 1 Disgust ██████████████████ 18 Anger ██████████████████████████████████████████████████████████████████ 63 Joy 0 Fear ████████████████ 15 Sadness Twitter_Sentiment:> sentiment --docsentiment +----------------+----------+----------+ | Sentiment Type | Score | if_mixed | +----------------+----------+----------+ | positive | 0.969859 | 1 | +----------------+----------+----------+- Running the fetch command with invalid username
Twitter_Sentiment:> fetch @invalidUsename 7 Invalid twitter username, try again with a valid username- Running the fetch command with no internet connection
Twitter_Sentiment:> fetch @invalidUsename 7 Invalid twitter username, try again with a valid username- Running the fetch command with a twitter handle whose tweets have been protected
Twitter_Sentiment:> fetch @protected_handle 7 You are not authorized to view this person tweets!, (protected tweets)