[1/N]
I wanted to analyse my Social Media data.
I exported my @Twitter data and analysed with the #OracleText in the #OracleAutonomousDatabase @OracleDatabase and @OracleAnalytics Cloud

Starting from the easy… which is the tweet with most likes?
hint: Becoming @oracleace #ACED!
[2/N]
Second question: which are the most used words when I tweet?

Easy, create an index (type CTXSYS.CONTEXT) in the @OracleDatabase

More info at

As expectable the most frequent words are around OUGs, Tech, Analytics, Oracle Products and Talks
[3/N]
How does it change when I reply to people?

Well, you can see that words about OUG sessions and Oracle are still there, but there is the emerging topic of #Food!
[4/N] Who do I interact most with?

I plotted the # of Replies to specific Users…
No wonder (at least to me) that I get most interaction with people that tag me with italian food abominations… Does it ring a bell @dw_pete, @HeliFromFinland, @stewartbryson and @connor_mc_d ?
[5/N]
So how do I reply them?

Again, very easy with #OracleAnalyticsCloud Trellis Options.
You can spot that #Food is the major discussion topic with @HeliFromFinland and @dw_pete, while my chats with @connor_mc_d and @stewartbryson are covering more topics
[6/N]
One Last mention to my interactions with @Nephentur:

It’s clear his love for OUGs, Airports, Flights, Hotels… all driven by #TheBergEffect
[7/N]
Useful Links:
- Download your twitter data: https://help.twitter.com/en/managing-your-account/how-to-download-your-twitter-archive

- Token analysis with #OAC part 1:

- Token analysis with #OAC part 2:
[8/N]

In a future #OracleAnalyticsCloud release we’ll see Token Analysis being a native step of #DataFlows within the #DataBaseAnalytics options

@oracleace @rittmanmead

Thanks to @philippe_lions for the hints on the index usage!
You can follow @FTisiot.
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