15 Tips for Using Python to Research Twitter Posts & Comments
Twitter is a very popular social network platform, with millions of people using it daily for news and to interact as covered over at runrex.com. With the large amounts of data available on the platform, Twitter can be an excellent tool for research and business. One of the tools that will help you uncover insights from the large amounts of data from the platform is Python, and this article will look to highlight tips for using it to research Twitter posts and comments.
- Twitter’s API
You need to know about Twitter’s API if you are to uncover any insights on posts and comments on the platform using Python since it will be the foundation of any such operation on the platform. According to guttulus.com, the official Twitter API will allow you to perform complex queries such as pulling every tweet about a certain topic or pulling a certain user’s tweets.
- Accessing Twitter’s API
If you want to access Twitter’s API, then you will need to create a developer account on the Developers page of Twitter’s site as outlined over at runrex.com. It is a pretty simple procedure that doesn’t require much initially other than a Twitter account.
- Authentication and access tokens
Once you create a developer account, then you will also need to obtain access tokens for you to be able to access the Twitter API. As is covered in detail over at guttulus.com, this is also pretty straightforward and shouldn’t take you that long to complete.
- Be careful with your consumer key and secret as well as your access token and secret
As is explained over at runrex.com, your consumer key and secret will be used to authenticate the app that is accessing and using the Twitter API. At the same time, the access token and secret will be used to authenticate the user. This means that these parameters should be treated like passwords and shouldn’t be included in any of your code in plain text.
- Python libraries for Twitter API
One of the reasons why Python is a popular choice for accessing the Twitter API is because you can find several libraries that will allow you to do just that. Examples of some of these libraries for the Twitter API include Tweepy, Twython, Python-Twitter, TwitterSearch, among others.
- Twython and why some prefer it
Twython is among the most popular Python libraries for the Twitter API according to guttulus.com. This has to do with the fact that it has diverse features that are aligned with different aspects of the Twitter API, it is mature having been available for at least 5 years now, as well as the fact that it supports the streaming of tweets.
- Tweepy and why some prefer it
Another very popular Python library for the Twitter API, according to the gurus over at runrex.com, is Tweepy. It is both straightforward to use and download, which is part of the reasons why it is so popular, and it also provides a convenient cursor interface to iterate through different types of objects, while also supporting the streaming of tweets.
- Installing Tweepy or Twython
The choice between Tweepy and Twython usually boils down to a matter of preference as they are both very good libraries for the Twitter API. The good news is that the simplest way to install both of them is by using pip as discussed over at guttulus.com, although other options are available, including using GitHub. Installing either of them should be pretty straightforward.
- You can pull tweets from your Twitter feed
With either Twython or Tweepy installed, one thing you will be able to do is to pull tweets from your Twitter feed. You can go as far back as 7 days, which will allow you to uncover useful insights and patterns as far as your timeline is concerned. Once you pull a tweet, you can find out accompanying information such as the location and name attribute of the tweeter as discussed over at runrex.com.
- You can pull tweets from a specific user
With Python, you can also pull the latest tweets from a specific user of your choice. This means that if there is a particular user that you want to research, you can use Python to access the Twitter API to pull their tweets and then use them to uncover useful insights.
- The number of tweets you can pull is limited
It is also important to note that as much as you may want to pull countless tweets going as far back as you want, the number of tweets that you can pull for each query is limited. This is because of Twitter’s rate limits, which are covered over at guttulus.com.
- Applications of pulling tweets from specific users
Some of the common applications of using Python to pull tweets from specific users include running analysis on specific users, monitoring the changes in a given user’s followers, finding Twitter influencers, and many others outlined over at runrex.com.
- Finding tweets using a keyword
You can also use Python to access the Twitter API and find recent tweets containing a specific keyword of interest as explained over at guttulus.com. Applications of this include where you want to see how your business is being mentioned on the platform or where you want to see people’s opinion on a given topic.
- Twitter sentiment analysis
Sentiment analysis, as covered over at runrex.com, is the process of computationally determining whether a piece of content is positive, negative, or neutral as far as users are concerned. Python, with the help of TextBlob, will allow you to conduct sentiment analysis to see if the overall opinion of your business or content is positive or negative.
- Visualization
When it comes to the visualization of your results, one of the options worth considering is WordCloud. This is always an excellent option to go with if you are working with text data as it will allow you to get a global vision of the data. For example, if you want to see which words appear most often in tweets on a particular topic, word clouds will help you achieve exactly that.
This discussion only just scratches the surface as far as this topic is concerned, and for more on this and other related topics please check out the excellent runrex.com and guttulus.com.