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

Agriculture is a sector influenced by myriad factors, from weather changes to global market dynamics. As developers and data scientists, we need an efficient way to gauge sentiment shifts in agriculture-related discussions. Traditional scraping methods for social media and news can be tedious and unreliable. This is where the Pulsebit API comes in handy.

The Problem (DIY scraping pain)

Scraping social media and news sites for sentiment analysis presents several challenges:

1. Frequent Changes: Websites update their structure, breaking your scraping logic.
2. Rate Limiting: Many sites limit the number of requests you can make in a specific timeframe.
3. Data Noise: Extracting meaningful sentiment from raw text can be a daunting task.

Instead of dealing with these frustrations, we can leverage the Pulsebit API to get structured sentiment data with a single endpoint call.

The Solution (Pulsebit API — one endpoint)

The Pulsebit API provides a neat solution for sentiment analysis. Using the /news_semantic endpoint, you can retrieve sentiment scores and analysis for various topics, including agriculture. With just one call, you can get comprehensive sentiment data without the overhead of scraping.

The Code (Python GET /news_semantic with code blocks)

To get started, you’ll need to install the requests library if you haven’t already:

pip install requests

Now, you can make a simple GET request to the Pulsebit API. Here’s how:

import requests

def get_agriculture_sentiment():
    # Define the API endpoint and parameters
    url = "https://api.pulsebit.co/news_semantic"
    params = {
        'topic': 'agriculture',
        'api_key': 'YOUR_API_KEY'  # Replace with your actual API key
    }

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

    if response.status_code == 200:
        return response.json()
    else:
        raise Exception(f"Error: {response.status_code}, {response.text}")

# Fetch and print agriculture sentiment
sentiment_data = get_agriculture_sentiment()
print(sentiment_data)

Replace 'YOUR_API_KEY' with your actual API key from Pulsebit.

Reading the Response

When you call the /news_semantic endpoint, you’ll receive a JSON response. Here’s a breakdown of the key fields based on sample data:

{
    "sentiment": {
        "agriculture": {
            "sentiment": 0.00,
            "momentum": 0.80,
            "clusters": 0,
            "confidence": 0.87
        }
    }
}

• sentiment: Overall sentiment score for agriculture (-1 to 1).
• momentum: Indicates the speed of change in sentiment (0 to 1).
• clusters: Number of distinct sentiment clusters identified.
• confidence: Confidence level of the sentiment score (0 to 1).

In the example above:

• Agriculture sentiment is neutral at 0.00.
• Momentum is high at 0.80, suggesting a potential change.
• There are 0 clusters, indicating a lack of diverse opinions.
• Confidence is robust at 0.87, signaling reliability.

Three Use Cases

1. Algo Alert: Set up an algorithm that triggers alerts when sentiment shifts significantly. For example, if the momentum exceeds 0.75, notify your trading system to adjust positions.

2. Slack Bot: Build a simple Slack bot that pings your team with the latest agriculture sentiment. This keeps your team informed without manual checks.

3. Dashboard: Create a dashboard using libraries like Dash or Streamlit to visualize sentiment trends over time. Incorporate real-time updates from the Pulsebit API.

Get Started

To learn more about the Pulsebit API and explore additional endpoints, visit the Pulsebit Documentation. This resource will guide you through authentication, advanced queries, and more.

By leveraging the Pulsebit API, you can enhance your agriculture data analysis without the headaches of DIY scraping. Happy coding!