Demo: Sentiment Analysis on Bluesky

8.6.3. Demo: Sentiment Analysis on Bluesky#

Choose Social Media Platform: Bluesky | Reddit | Discord | No Coding

Now let’s try using sentiment analysis (and loop variables) on Bluesky:

Normal Bluesky Setup#

Now we can continue logging in to Bluesky and look through multiple posts.

load atproto library#

# Load some code called "Client" from the "atproto" library that will help us work with Bluesky
from atproto import Client

(optional) make a fake Bluesky connection with the fake_atproto library#

For testing purposes, we”ve added this line of code, which loads a fake version of atproto, so it wont actually connect to Bluesky. If you want to try to actually connect to Bluesky, don’t run this line of code.

%run ../../fake_apis/fake_atproto.ipynb

Fake atproto (bsky.app) is replacing the atproto.blue library. Fake atproto doesn't need real passwords, and prevents you from accessing real Bluesky

login to Bluesky#

# Login to Bluesky
# TODO: put your account name and password below

client = Client(base_url="https://bsky.social")
client.login("your_account_name.bsky.social", "m#5@_fake_bsky_password_$%Ds")

Fake atproto is pretending to set up a client connection to: https://bsky.social

Fake atproto is pretending log into your account: your_account_name.bsky.social

Do a search for posts on Bluesky#

We’ll now search for posts on Bluesky

Note: If you run this on real Bluesky, we canâ€™t gurantee anything about how offensive what you might find is.

search_query = "news"
search_results = client.app.bsky.feed.search_posts({'q': search_query}).posts

Sentiment Analysis#

load sentiment analysis library and make analyzer#

import nltk
nltk.download(["vader_lexicon"])
from nltk.sentiment import SentimentIntensityAnalyzer
sia = SentimentIntensityAnalyzer()

[nltk_data] Downloading package vader_lexicon to
[nltk_data]     C:\Users\kmthayer\AppData\Roaming\nltk_data...
[nltk_data]   Package vader_lexicon is already up-to-date!

loop through posts, finding average sentiment#

We can now combine our previous examples of looping through the posts with what we just learned of sentiment analysis and looping variables to find the average sentiment of a set of posts.

num_posts = 0
total_sentiment = 0

for post in search_results:
    
    #calculate sentiment
    post_sentiment = sia.polarity_scores(post.record.text)["compound"]
    num_posts += 1
    total_sentiment += post_sentiment

    print("Sentiment: " + str(post_sentiment))
    print("   post text: " + post.record.text)
    print()


average_sentiment = total_sentiment / num_posts
print("Average sentiment was " + str(average_sentiment))

Sentiment: 0.784
   post text: Breaking news: A lovely cat took a nice long nap today!

Sentiment: 0.0
   post text: Breaking news: Someone said a really mean thing on the internet today!

Sentiment: 0.7088
   post text: Breaking news: Some grandparents made some yummy cookies for all the kids to share!

Sentiment: -0.6114
   post text: Breaking news: All the horrors of the universe revealed at last!

Average sentiment was 0.22034999999999996

We can now see the average sentiment of a set of bluesky posts!

If you use your bluesky bot keys, you can change the search_query to be whatever one you want and see whether people are posting positively or negatively in it.

Alternately look up a feed instead of a search#

We can also look up a feed instead of runnign a search

There are some subtle differences with how things come back, and therefore how we get the text out of the post (basically we get back a list of post_info, instead of a list of posts)

Before we begin though, we need a helper function.

helper function for atproto feed links#

NOTE: You don’t need to worry about the details of how this works, it just is here to make the code later easier to use.

import re #load a "regular expression" library for helping to parse text
from atproto import IdResolver # Load the atproto IdResolver library to get offical ATProto user IDs

# function to convert a feed from a weblink url to the special atproto "at" URI
def get_at_feed_link_from_url(url):
    
    # Get the user did and feed id from the weblink url
    match = re.search(r'https://bsky.app/profile/([^/]+)/feed/([^/]+)', url)
    if not match:
        raise ValueError("Invalid Bluesky feed URL format.")
    user_handle, feed_id = match.groups()

    # Get the official atproto user ID (did) from the handle
    resolver = IdResolver()
    did = resolver.handle.resolve(user_handle)
    if not did:
        raise ValueError(f'Could not resolve DID for handle "{user_handle}".')

    # Construct the at:// URI
    post_uri = f"at://{did}/app.bsky.feed.generator/{feed_id}"

    return post_uri

load posts from a feed#

Now we can put in a feed url weblink and load the recent posts from that feed. Below we have a link to an Animals feed. You can change the feed_url to another feed if you want.