To enhance our understanding of user sentiment within Telegram channels and private messages, we propose the development of a feature that scrapes Telegram messages and performs sentiment analysis on the collected data.
Goals
Scrape messages from specified Telegram channels and private chats.
Analyze the sentiment of the messages to gauge user sentiment trends.
Provide insights that can help in community management and marketing strategies.
Requirements
Develop or integrate a Telegram bot capable of reading messages from channels and private chats.
Ensure compliance with Telegram's API usage policies and data privacy regulations.
Implement a sentiment analysis model or use a third-party service to evaluate message sentiments.
Store the results in a structured format for further analysis and reporting.
Potential Challenges
Ensuring the bot only operates in channels and chats where it has explicit permission to scrape messages.
Dealing with various languages and the nuances of sentiment analysis.
Managing the volume of messages and the performance of the sentiment analysis process.
Compliance and Security
Review and adhere to Telegram's API terms and privacy policies.
Ensure that user consent is obtained before scraping private messages.
Implement data encryption and secure storage practices for sensitive data.
Summary
To enhance our understanding of user sentiment within Telegram channels and private messages, we propose the development of a feature that scrapes Telegram messages and performs sentiment analysis on the collected data.
Goals
Requirements
Potential Challenges
Compliance and Security
Resources
Acceptance Criteria