From Big Social Data to Smart Social Data
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From Big Social Data to Smart Social Data
- 1. Big Social Data From Big Data to Smart Data Prinzie Anita solutions-2 Belgium www.solutions2.be +32(0)9 242 50 40 Solutions-2 London www.solutions2.co.uk +44 (0)20 7608 9300
- 2. OR 50,000 100,000 125,000 150,000
- 3. OR 650,000 100,000 48 hours 28,000
- 5. ORGANIC DATA DESIGNED DATA CREATED TO GAIN SPECIFIC INSIGHTS DATA RICHNESS Based on Bob Groves, former US Census director
- 6. BIG DATA SMART DATA
- 7. Define business objective
- 8. LISTENING MONITORING Brand perceptions Detecting crisis Brand positioning Complaints & malfunctions Consumer segments New product launch Media campaign success ... ... Based on Jasper Snyder Converseon
- 10. BUSINESS OBJECTIVE LISTENING PURPOSE MONITORING PURPOSE RELEVANT DATA Who? Which platforms? Which conversations? How long?
- 11. Who Fit with business objective IPhone 5 UK launch success (Vision Critical) “Should we listen to FB conversations of people not wanting the IPhone 5?” Battery 8 3 44 65 Negative Neutral Positive 53 27 All Want IPhone 5 11
- 12. Who & Which platforms Profile on channel usage & engagement 15-24 25-34 35-54 55-99 Actively engaging on FB, Twitter, blogs?
- 13. Which conversations Find the most relevant ones B2B Software Adoption Journey Focus groups with B2B customers Dictionary of typical actions during different phases of the software adoption process Scoring all Twitter/blog conversations on the software adoption phases. Software adoption journey-conversations 13
- 14. How long? Find relevant time window Natural time window ‘Enough conversations’ time window New product launch: 90 days before and after (Microsoft) 14
- 16. Clean and Preprocess Keep goal in mind Keep emoticons and markup for detecting crisis Context specific normalization and annotation (e.g. Convey API) 16
- 18. MONITORING PURPOSE SENTIMENT ANALYSIS Detecting crisis Detecting gradations of negative and evolutions Identifying complaints Detecting gradations of and malfunctions negative Monitoring response to Detecting gradations of new product launch positive and negative 18
- 19. Remedies Correct 80% Cost-sensitive learning Undersampling of neutral class 90% Use recall, precision and F1 measure to 7% 3% evaluate model Positive Neutral Negative 19
- 20. Validate results
- 21. Validate social media results Denali The evolution of the Microsoft software adoption index did O365 follow known success/failure trends for past software launches. 21
- 22. BIG DATA Define business objective Identify relevant data Clean & preprocess Analyse with objective in mind Validate results SMART DATA
- 23. Anita Prinzie anita@solutions2.be @AnitaPrinzie If you have any risingquestions
- 24. References http://www.domo.com/blog/2012/06/how-much-data-is-created- every-minute/ Snyder, J. (2012), Enriching Social Data for Market Research Converseon, 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. 24
Notes de l'éditeur
- So in a nutshell. To convert big social data into smart social data you follow a five step process.In the first step, you clearly define your business objective so you know whether you need social media listening or social media monitoring.In the second step, you identify the “relevant” social media data.In the third step, you clean and preprocess this “relevant” social media data perhaps with .In the fourth step, you analyse your cleaned “relevant” social media data with your business objective in mind.In the fifth step, you validate your social media results.So, now you have smart social data!