Analyzing Social Media Data in Python
In this course, you'll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.
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Course Description
Twitter produces hundreds of million messages per day, with people around the world discussing sports, politics, business, and entertainment. You can access thousands of messages flowing in this stream in a matter of minutes. In this course, you will learn how to collect Twitter data and analyze tweet text, Twitter networks, and the geographical origin of the tweet. We'll be doing this with datasets on tech companies, data science hashtags, and the 2018 State of the Union address. Using these methods, you will be able to inform business and political decision-making by discovering the prevalence of important topics, the diversity of discussion networks, and a topic's geographical reach.
- 1
Basics of Analyzing Twitter Data
FreeWhy analyze Twitter, how to access Twitter APIs, and understanding Twitter JSON.
Analyzing Twitter data50 xpWhy Analyze Twitter Data?50 xpUses of Twitter analysis50 xpCollecting data through the Twitter API50 xpTwitter APIs50 xpSetting up tweepy authentication100 xpCollecting data on keywords100 xpUnderstanding Twitter JSON50 xpLoading and accessing tweets100 xpAccessing user data100 xpAccessing retweet data100 xp - 2
Processing Twitter text
How to process Twitter text.
Processing Twitter text50 xpTweet Items and Tweet Flattening100 xpA tweet flattening function100 xpLoading tweets into a DataFrame100 xpCounting words50 xpFinding keywords100 xpLooking for text in all the wrong places100 xpComparing #python to #rstats100 xpTime series50 xpCreating time series data frame100 xpGenerating mean frequency100 xpPlotting mean frequency100 xpSentiment analysis50 xpLoading VADER100 xpCalculating sentiment scores100 xpPlotting sentiment scores100 xp - 3
Twitter Networks
Network analysis with Twitter data.
Twitter networks50 xpTypes of Twitter networks50 xpWhich direction is the arrow?50 xpImporting and visualizing Twitter networks50 xpCreating retweet network100 xpCreating reply network100 xpVisualizing retweet network100 xpIndividual-level network metrics50 xpIn-degree centrality100 xpBetweenness centrality100 xpRatios100 xp - 4
Putting Twitter data on the map
How to map Twitter data.
Maps and Twitter data50 xpMotivations50 xpComparisons50 xpGeographical data in Twitter JSON50 xpCoordinates and bounding boxes50 xpAccessing user-defined location100 xpAccessing bounding box100 xpCalculating the centroid100 xpCreating Twitter maps50 xpCreating Basemap map100 xpPlotting centroid coordinates100 xpColoring by sentiment100 xpCongratulations!50 xp
In the following tracks
Marketing AnalyticsDatasets
Data Science Hashtag datasetState of the Union Reply Network datasetState of the Union Retweet Networking dataset
David Campos
Greg Wilson
Kara Woo
Eunkyung Park
Shon InouyePrerequisites
Data Manipulation with pandas
Alex Hanna
Computational Social Scientist
Alex Hanna is a computational social scientist working in the areas of politics, natural language processing, and fairness in machine learning and artificial intelligence.
What do other learners have to say?
I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.
Devon Edwards Joseph
Lloyds Banking Group
DataCamp is the top resource I recommend for learning data science.
Louis Maiden
Harvard Business School
DataCamp is by far my favorite website to learn from.
Ronald Bowers
Decision Science Analytics, USAA
Join over 9 million learners and start Analyzing Social Media Data in Python today!
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By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA. You confirm you are at least 16 years old (13 if you are an authorized Classrooms user).