![]() In the project dashboard, click “ENABLE APIS AND SERVICES”, and search for Cloud Natural Language API.Ĭlick “ENABLE” to enable the API. Go to Google Developers Console and create a new project (or select the one you have). We need to enable the Google Natural Language API first if we want to use the service. Great! Now you should have four keys - API Key, API Secret Key, Access Token, and Access Token Secret. Copy the Access Token and Access Token Secret that have been generated. Open Apps page, click “Create an app”, fill out the form and click “Create”.Ĭlick on “Keys and tokens” tab, copy the API Key and API Secret Key in the “Consumer API keys” section.Ĭlick the “Create” button under “Access token & access token secret” section. Go to Twitter Developer website, and create an account if you don’t have one. To be able to gather the tweets from Twitter, we need to create a developer account to get the Twitter API Keys first. pip3 install tweepy nltk google-cloud-language python-telegram-bot 2. python-telegram-bot will send the result through Telegram chat. Google Natural Language API will do the sentiment analysis. We will use nltk to help us clean the tweets. We are going to use tweepy to gather the tweet data. If this is your first time building a Telegram Bot, you might want to read this post first. In this tutorial, we are going to make a Telegram Bot that will do the sentiment analysis of tweets related to the keyword that we define. But wouldn’t it be cool if we could make our own sentiment analyzer? Let’s make it then! You might want to use a sentiment analyzer like MonkeyLearn or Talkwalker. Maybe your company launched a new product and you want to know how people reacted to it. Imagine you are a product owner who wants to know what people are saying about your product in social media.
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