Observing how hashtags evolve over time

[Sydney Zheng]

Hello all,

I am interested in using ORA to observe how the hashtag network evolves over time.

Currently, I have Twitter data for roughly one month, which is split into four-hour intervals. I was going through each of these 4-hour interval meta-networks to study the relationship among the hashtags.

However, this method is both slow and makes it difficult to understand how network structure is preserved over time.  For example, in doing this manual examination, I may miss that a 4-clique reappears at certain points in time, or that a hashtag is growing in centrality.

I was wondering what more sophisticated techniques I could use to study how the hashtag network evolves over time to better understand what events are occurring around people in real time?

Thanks!

Sydney

[Kathleen Carley]

first do it on a one day not 4 hour basis

second - looking at these over time is hard - what you need to do is use the network over time visualizer in ora

third you need to use the key entity report and put each day of data in and then let it show you the trends -

please note you are hitting the  limits of the current science and need to start with things like - who are the key actors and have they changes 

what is the volatility of the key actors

which are bots

what are the key hashtags and have they changes

what is the volatility of the hashtags

then move to dyads and then to triplets

you need to attend the remote network science casos summer institute in June - please register now and I will cover the cost

 

--
Computational Analysis of Social and Organizational Systems (CASOS)
The Institute for Software Research, Department of Computer Science
Carnegie Mellon University, Pittsburgh, PA, USA
http://casos.cs.cmu.edu/
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[Sydney Zheng]

Sounds great.  What is the proper way I should register for that then?

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[Kathleen Carley]

look at the casos website and/or talk to sienna

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