Python Social Media Analytics

Applying Alchemy API

In order to use the Alchemy API we will first create a function that makes the requests to the service:

import requests 
import json 
 
apikey = "YOUR_KEY" 
 
url = "https://gateway-a.watsonplatform.net/calls/text/TextGetEmotion" 
 
def get_alchemy(apikey,text): 
    pms = {'apikey' : apikey, 'outputMode' : 'json', "text" : text} 
    result = requests.post(url, data = pms) 
    try: 
        emotions = json.loads(result.text)['docEmotions'] 
    except: 
        emotions = None 
    return(emotions) 

The free version of the alchemy API is limited to 1000 requests per month. For our analysis, we will take the first 1000 comments:

alchemy = df_comments.head(1000) 

Then, we apply the alchemy API on each message in our dataset using the apply method. We store the results ...