#1

I’m a current final year UK undergraduate student. I am waiting for my research API access.
I am currently using Tweepy in python to find keyword related tweets and assign sentiment values.
Could anyone suggest any other libraries in Python or if they found Tweepy was inefficient.
I tried rTweet and BeautifulSoup but found Tweepy was the easiest way and fastest way to code to get keyword related tweets.

#2

Try twarc in the command line, no code required, just specify the query and it will write out the json, and you can convert it to CSV for analysis:

#3

Hi, thank you so much for your reply.

My academic research application got rejected and so I can only analyse 2 million tweets.
My programming experience is quite new so would Twarc be able to collect 2 million tweets or if there is any other library that could collect 2 million tweets like Tweepy. Which then could be exported to a csv file etc so I can apply a sentiment value to the tweets?

#4

Twarc2 commands will still work without academic access, but you won’t be able to specify --archive and search older than 7 days tweets

#5

I am currently using Tweepy in python to find keyword related tweets and assign sentiment values. Could anyone suggest any other libraries in Python .
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#6

An alternative to tweepy is twarc, Examples of using twarc2 as a library - twarc and for sentiment a good one to try is Vader GitHub - cjhutto/vaderSentiment: VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.