Twitter analytics in Bluemix

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Analyze Twitter data completely in Bluemix. Collect data, add sentiment, copy to in-memory database, analyze with R or WatsonAnalytics. All in the cloud.

Technology

© 2015 IBM Corporation1
Wilfried
Hoge

IT
Architect
Big
Data

@wilfriedhoge

Twi.er
Analy3cs
in
Bluemix

© 2015 IBM Corporation2
Collect
data
with

Node
Red

Add
sen:ment

with
Text
Analy:cs

In
BigInsights

Bring
data
to
DashDB

for
ad-‐hoc
analysis

Analyze
with
R

In
RStudio

Analyze
with

WatsonAnaly:cs

Run
on
Bluemix

© 2015 IBM Corporation3
Start
from
Bluemix
Dashboard

© 2015 IBM Corporation4
Node
Red
applica3on
with
bound
services

© 2015 IBM Corporation5
Node
Red:
Collect
Twi.er
data
and
write
to
HDFS

© 2015 IBM Corporation6
Open
bound
Hadoop
service
–
BigInsights

© 2015 IBM Corporation7
Find
wri.en
Tweets
in
HDFS
–
JSON
format

© 2015 IBM Corporation8
Bring
schema
on-‐read
to
the
data

© 2015 IBM Corporation9
Add
sen3ment
with
text
analy3cs
in
BigSheets

© 2015 IBM Corporation10
Twi.er
data
with
sen3ment
in
BigSheets

© 2015 IBM Corporation11
Copy
data
to
DashDB
for
further
analysis

© 2015 IBM Corporation12
Open
DashDB
from
Bluemix
Dashboard

© 2015 IBM Corporation13
Have
the
Twi.er
data
ready
for
analysis

© 2015 IBM Corporation14
Start
RStudio
directly
from
DashDB

© 2015 IBM Corporation15
Run
R
Scripts
on
Twi.er
data
in
DashDB

© 2015 IBM Corporation16
Ask
Watson
Analy3cs
to
help
analyzing

© 2015 IBM Corporation17
Watson
Analy3cs
suggests
a
result

© 2015 IBM Corporation18
What
is
Watson
Analy:cs?

What
is
DashDB?

“Great movie with a nice story!” What do you think, did the person like the film or hate it? Most of the time it’s easy for us to decide whether the message of a text is positive or negative. But what if you wanted to automate the process of understanding the sentiment? For example, if you have a lot of customers leaving comments, or people publishing movie reviews, you will want to discern the sentiment and find out who is posting positive or negative messages. Sentiment analysis is an important piece of many data analytics use cases. Whether it processes customer feedback, movie reviews, or tweets, sentiment scores often contribute an important piece to describing the whole scenario. These are just some examples of a long list of use cases for sentiment analysis, which includes social media analysis, 360 degree customer views, customer intelligence, competitive analysis and many more. To avoid doing this manually, we apply sentiment analysis and teach an algorithm to understand text and extract the sentiment using Natural Language Processing. A copy of the webinar can be viewed at https://www.youtube.com/watch?v=By4IZeIzxIw

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Transcript: Selling digital books in 2024: Insights from industry leaders - T...

BookNet Canada

The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more. Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/ Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.

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Transcript: Selling digital books in 2024: Insights from industry leaders - T...