Mining Creative Communities with Twitter Data

MINING CREATIVE COMMUNITIES WITH TWITTER DATA CECHR Symposium 2016

CECHR INCUBATOR FUND PROJECT • Dimitrios Efstathiou • Kit Macleod kit.macleod@hutton.ac.uk • Susan Mains • Mel Woods • Andy Cobley a.e.cobley@dundee.ac.uk

WHAT DID WE WANT TO FIND OUT • How are creative communities influenced by place and environment • Twitter is used as the environment • Three outcomes • Graphical interactions • Analyzing the language of Creatives • Visualizations of interactions

GRAPHICAL INTERACTIONS • We used a graph database to store and analyze tweets • Who Tweeted Who ?

• How far do these interactions happen ?

http://catc3h.cloudapp.net/

ANALYZING THE LANGUAGE OF CREATIVES • Is there an ontology for creativity?

• Building on the work of Jordanousa, A., & Kellerb, B. • Tweets are processed through natural Language Toolkit • Data Stored in a Document Database (MongoDb) and processed by R

WORD CLOUD

VISUAL ANALYSIS • OLAP cube for tweet Analysis • Commonly used for marketing • Once created visualization tools (Tableau) can be used to explore the data

HASHTAG ANALYSIS

DATA PIPELINE • Data flows from twitter through this system • Always up to date • Can see it at http://catc3h.cloudapp.net/ • Data is not live now.

THANKS • Thanks to CECHR • Kit For driving this forward • Dimitrios for all the hard work !