from big social data to smart social data
DESCRIPTION
Research Arena 2012TRANSCRIPT
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Big Social DataFrom Big Data to Smart Data
Prinzie Anita
Click icon to add picture
125,000
100,000
1 MINUTE
50,000
OR
150,000
48 hours
100,000
1 MINUTE
650,000 28,000
OR
http://datasift.com/stream/13991/mcdonalds#app1-preview
ORGANIC DATA DESIGNED DATA
Based on Bob Groves, former US Census director
CREATED TO GAIN SPECIFIC INSIGHTSDATA RICHNESS
BIG DATA SMART DATA?
Define business objective
Brand perceptions Detecting crisis
Complaints & malfunctions
New product launchConsumer segments
Media campaign success
Based on Jasper Snyder Converseon
MONITORINGLISTENING
Brand positioning
...
...
Identify relevant data
Who?
Which conversations?How long?
LISTENING PURPOSE
RELEVANT DATA
MONITORING PURPOSE
BUSINESS OBJECTIVE
Which platforms?
11
WhoFit with business objective
IPhone 5 UK launch success (Vision Critical)“Should we listen to FB conversations of people not wanting the IPhone 5?”
All Want IPhone 5
2753
6544
8 3
NegativeNeutralPositive
Battery
Profile on channel usage & engagement
15-24 25-34 35-54 55-99
Actively engaging on FB, Twitter, blogs?
Who & Which platforms
13
Which conversationsFind the most relevant ones
Dictionary of typical actions during different phases of the software adoption process
Focus groups with B2B customers
Scoring all Twitter/blog conversations on the software adoption phases.
B2B Software Adoption Journey
Software adoption journey-conversations
14
How long?Find relevant time window
Natural time window
‘Enough conversations’ time window
New product launch: 90 days before and after (Microsoft)
Clean & Preprocess
16
Clean and Preprocess
Keep emoticons and markup for detecting crisis
Context specific normalization and annotation (e.g. Convey API)
Keep goal in mind
Analyse withobjective in mind
18
Detecting crisis
Identifying complaints and malfunctions
Monitoring response to new product launch
Detecting gradations of negative and evolutionsDetecting gradations of negative
Detecting gradations of positive and negative
SENTIMENT ANALYSISMONITORING PURPOSE
19
Remedies
Cost-sensitive learning
Undersampling of neutral class
Use recall, precision and F1 measure to evaluate model
Correct80%
Positive Neutral Negative7%
90%
3%
Validate results
21
Validate social media results
The evolution of the Microsoft
software adoption index did
follow known success/failure
trends for past software
launches.-90 -60 -30 Launch 30 60 90
Denali
O365
SMART DATA
Define business objective
Identify relevant dataClean & preprocess
Analyse with objective in mindValidate results
BIG DATA
12345
24
References
http://www.domo.com/blog/2012/06/how-much-data-is-created-every-minute/
Snyder, J. (2012), Enriching Social Data for Market ResearchConverseon, New MR Webinar, Social Media Research, October 9th 2012.
Woolmer, J. (2012), Is it real? Using conventional research to validate and quantify social media findings, Vision Critical, New MR Webinar, Social Media Research, October 9th 2012.