How to Detect Space Sentiment Shifts with the Pulsebit API (Python)

In the world of finance and trading, sentiment analysis can provide valuable insights into market movements. However, when it comes to niche sectors like space exploration, scraping data from various sources manually can be a tedious task. Enter the Pulsebit API, a tool designed to help you get sentiment data effortlessly. In this article, we'll explore how to leverage this API to detect sentiment shifts in the space sector.

The Problem (DIY scraping pain)

If you've ever tried to scrape sentiment data from social media or news sites manually, you know the pain. You have to deal with rate limits, changing HTML structures, and the constant threat of IP bans. Not to mention, the data you collect often lacks the richness and nuance you need for accurate sentiment analysis.

For instance, tracking space sentiment requires you to gather information from multiple sources, analyze it, and then determine how the sentiment is shifting over time. This is not just cumbersome; it’s also prone to errors.

The Solution (Pulsebit API — one endpoint)

The Pulsebit API provides a streamlined solution to this problem with a single endpoint called /news_semantic. It aggregates sentiment data from various sources, allowing you to focus on analysis instead of scraping.

With just a few lines of code, you can get the latest sentiment data for the space sector and watch for shifts that could indicate market movements.

The Code (Python GET /news_semantic)

To get started, you’ll need to have Python installed along with the requests library. If you don’t have requests, you can install it via pip:

pip install requests

Here’s how to call the Pulsebit API and retrieve sentiment data for the space sector:

import requests

def get_space_sentiment():
    url = "https://api.pulsebit.co/news_semantic"
    params = {
        "category": "space"
    }

    response = requests.get(url, params=params)

    if response.status_code == 200:
        return response.json()
    else:
        raise Exception(f"API call failed with status code {response.status_code}")

data = get_space_sentiment()
print(data)

Reading the Response

The response from the API will provide several fields. Let’s break down what to expect:

• sentiment: This is the overall sentiment score for space, which can range from -1 (very negative) to +1 (very positive). For example, a sentiment of +0.00 indicates neutrality.

• momentum: This indicates the rate of change in sentiment. A value of +0.44 suggests that the sentiment is gaining traction positively.

• clusters: This tells you how many unique sentiment clusters have been identified. A value of 0 means no clusters were detected, indicating a lack of strong opinions.

• confidence: The confidence level of the sentiment score, ranging from 0 to 1. A confidence of 0.87 means the data is quite reliable.

Three Use Cases

1. Algo Alert: Set up a simple algorithmic trading alert. If the sentiment momentum crosses a certain threshold, trigger a buy or sell action.

   if data['momentum'] > 0.5:
       print("Consider buying space stocks!")

1. Slack Bot: Create a Slack bot that sends daily updates on space sentiment. This keeps your team informed without needing to check data manually.

   import slack_sdk

   client = slack_sdk.WebClient(token='YOUR_SLACK_TOKEN')

   client.chat_postMessage(
       channel='#general',
       text=f"Current Space Sentiment: {data['sentiment']} (Momentum: {data['momentum']})"
   )

1. Dashboard: Visualize sentiment shifts over time on a dashboard using libraries like Dash or Streamlit. This can help in making informed decisions based on trends.

Get Started

To learn more about the Pulsebit API and how it can fit into your projects, check out their documentation at pulsebit.co/docs. The API is straightforward to use, and the potential applications are vast.

By using the Pulsebit API, you can shift your focus from scraping to analysis, making you more efficient in your development efforts. Happy coding!