Everyone Can Improve a Life

iamkilroy — Tue, 13 Oct 2020 00:56:14 +0000

A bit of a #humblebrag but I'm very proud to share...

My youngest son recently concluded his first ever fundraising activity for the American Foundation for Suicide Prevention, that he organized and led with the support of several of his Twitch streaming and gaming friends. Together and with the help of their various communities, they drove $600.00 in donations to an organization that is battling a problem which has directly impacted our family and so many others.

My help in that idea and execution? None. I found out an hour before he started his first charity game stream that he had put this together. I donated. I wasn't even the top donor. He and his friends had 30+ donors over 3 weeks pitching in everything from a couple dollars to a lot more. It all helped. And many more spread the word or contributed their time.

I like to think that I've been an example for his sense of giving and helping where there is need. In my own case I was inspired by a 20 year career at Microsoft, their matching of employee volunteer hours with cash, and dollar for dollar donation matching. And behind their philanthropic giving culture and helping where help is needed - is Bill Gates.

Everyone can have an impact on someone's life or need or circumstance. It just takes the desire and the willingness to put in the work.

Well done kid. Now please step away from the screen and go outside and play for a while.

"If you can't feed a hundred people, then feed just one." -Mother Teresa

First post... Sentiment Scoring in Python with Amazon Comprehend Service

iamkilroy — Sun, 11 Oct 2020 19:20:49 +0000

Here is an easy sentiment scoring sample that demonstrates how to calculate sentiment in stock tweets. It's probably not a fast track to stock market riches.

I pulled this code from the Amazon SageMaker Notebook I've been tinkering with. It should be pretty easy to get running using Tweepy for pulling tweets and the Amazon Comprehend NLP service to score.

import boto3
import tweepy

// Get your API keys from your Twitter developer dashboard
api_key = 'twitter-api-key'
api_secret = 'twitter-secret-api-key'
access_token = 'twitter-access-token'
access_token_secret = 'twitter-access-token-secret'

// Twitter Auth
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)

api = tweepy.API(auth)

# Define the search term and the date_since date as variables
stock_symbol = '$tsla'
since_date = '2020-10-08'

# Get stock tweets
tweets = tweepy.Cursor(api.search,
              q = stock_symbol,
              lang = 'en',
              since = since_date).items(10)

// Get Comprehend client
client = boto3.client('comprehend')

# Score and print tweets
for tweet in tweets:
    response = client.detect_sentiment(Text = tweet.text, LanguageCode = 'en')
    print(response, tweet.text)

Output will likely have mostly neutral scores and the occasional positive, negative, or mixed.

Sample positive output:

{'Sentiment': 'POSITIVE', 'SentimentScore': {'Positive': 0.6346455216407776, 'Negative': 0.022199517115950584, 'Neutral': 0.3431503474712372, 'Mixed': 4.635075583792059e-06}, 'ResponseMetadata': {'RequestId': '676a38f1-9ba3-4276-b883-8eb0f1594962', 'HTTPStatusCode': 200, 'HTTPHeaders': {'x-amzn-requestid': '676a38f1-9ba3-4276-b883-8eb0f1594962', 'content-type': 'application/x-amz-json-1.1', 'content-length': '163', 'date': 'Fri, 09 Oct 2020 02:53:41 GMT'}, 'RetryAttempts': 0}} $RH nice setup is brewing, supporting off of the 20 EMA. look for a few more days to support at this level for a m…

Good luck and have fun with some easy sentiment scoring.

DEV Community: iamkilroy

Everyone Can Improve a Life

First post... Sentiment Scoring in Python with Amazon Comprehend Service