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You can see individual Tweet performance, as well as recent months or a 28-day overview of cumulative impressions.Ĭapitalize on this information by repurposing Tweets that gained the most impressions, or creating Tweets on a similar subject. Under the Tweets section, you can find a list of all your Tweets and the number of impressions. Be sure to engage with followers that are asking questions or leaving reviews about your products or services. Top tip: The mentions section of your analytics dashboard can be a great customer service tool for your brand. Your top mention is also displayed each month, calculated by engagement, with a link that drops you directly into that Tweet for extra context. Similar to the profile visits metric, you can also view your over the last 28 days and over time. ![]() This can help you monitor if the amount of people visiting your profile is going up or down, so you plan and adjust your Tweets accordingly. It also shows how it compares to the last 28-day period, along with a mini graph displaying this data over time. This number is reflected across a 28-day period and is updated daily. The number of visits to your Twitter profile is displayed at the top of your analytics dashboard. Use this data to optimize your future Twitter campaigns and get better results.īelow, we've got eight things you can learn from your Twitter data: Twitter analytics shows you how your audience is responding to your content, what's working, and what's not. Every word, photo, video, and follower can have an impact on your strategy. With so many boxes to tick, it’s a good thing Twitter provides insights to help you understand your followers and the Twitter community as a whole. You need great copy, engaging creatives, clever use of keywords and hashtags, and content that is truly useful and valuable to your audience. #Twitter insights series#You can apply additional search criteria to include restricting to a date range, number of tweets to return, etcĬheck out the other blog posts in this series of Twitter Analytics using Python.Perfecting your Twitter content strategy to ensure it achieves your marketing objectives is no simple task. The following is an example of searching for a hash tag.įor tweet in tweepy.Cursor(api.search,q="#machinelearning", This can be hash tags, particular phrases, users, etc. Tweepy comes with a Search function that allows you to specify some text you want to search for. The following will take the last 10 tweets.įor tweets in tweepy.Cursor(api.home_timeline).items(10):Īn alternative is, that returns only 20 records, where the example above can return X number of tweets. You can also start listing the last X number of tweets from your timeline. Print('Listed: ' + str(user.listed_count)) Print('Followers: ' + str(user.followers_count)) Print('Twitter Name: ' + user.screen_name) #Get twitter information about my twitter account The following is an example about my Twitter account. There is a API function called 'me' that gathers are the user object details from Twitter and from there you can print these out to screen or do some other things with them. The easiest way to start exploring twitter is to find out information about your own twitter account. After that you will need to use the important codes that were defined on the Twitter webpage produced in Step 1 above, to create an authorised connection to the Twitter API.Īfter you have filled in your consumer and access token values and run this code, you will not get any response. The first thing you need to do is to import the tweepy library. #Twitter insights code#You are all set to start writing Python code to access, process and analyse Tweets. Step 3 - Initial Python code and connecting to Twitter ![]() #Twitter insights install#It will download and install tweepy and any dependencies. ![]() #Twitter insights full#Make sure to check out the Tweepy web site for full details of what it will allow you to do. There is the Tweepy library that is very popular. Step 2 - Install libraries for processing Twitter DataĪs with most languages there is a bunch of code and libraries available for you to use. The details contained on this web page (and below what is shown in the above image) will allow you to use the Twitter REST APIs to interact with the Twitter service. Keep the information on this page safe as you will need it later when creating your connection to Twitter. You will then get a web page like the following that contains lots of very important information. Then click the 'Create your Twitter Application' button. Then give the Name of your app (Twitter Analytics using Python), a description, a webpage link (eg your blog or something else), click on the 'add a Callback URL' button and finally click the check box to agree with the Developer Agreement. ![]()
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