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My presentation at #ThinkPH 'The Internet, Big Data and You' Conference, on August 23, 2013 at New World Hotel, Makati. Click here to see the #ThinkPH conference details and agenda: http://www.rappler.com/bulletin-board/36539-agenda-rappler-google-thinkph-internet-big-data-conference Event hosted by Rappler, Google and SocialGood. My slides cover: 1. Why analyze sentiment? 2. How does sentiment analysis work? 3. Practical applications 4. Sentiment of #ThinkPH Conference
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Presents to
Robin Leonard CEO, AllFamous Digital
robin_allfamous
robinleonard1
SENTIMENT ANALYSIS
Click here to see the agenda and conference details
Agenda
1. Why Analyze Sentiment? 2. Sentiment Analysis 101 3. Practical Applications 4. Sentiment of #ThinkPH
Agenda
1. Why Analyze Sentiment? 2. Sentiment Analysis 101 3. Practical Applications 4. Sentiment of #ThinkPH
Why Analyze Sentiment?
Emotions are core to purchase decisions
vs.
http://www.today.mccombs.utexas.edu/2010/04/do-you-make-buying-decisions-based-on-logic-or-emotion-a-tale-of-two-chickens
Social Media creates lots of data
Just waiting to become useful information
Consumers are FINALLY empowered
The Anatomy of a Crisis – The Incident
The Anatomy of a Crisis – The Impact
The Anatomy of a Crisis – The Response
The Anatomy of a Crisis – The Result
http://adage.com/article/digital/mckinsey-finds-social-buzz-affect-sales-negatively/242039/
Yes, Sentiment Impacts Sales
Agenda
1. Why Analyze Sentiment? 2. Sentiment Analysis 101 3. Practical Applications 4. Sentiment of #ThinkPH
What is Sentiment?
What is Sentiment?
emotions opinions intent
Subjective impressions, not facts
Example 1: Happy Mention
subject emotion brand
product
service
Example 2: Unhappy Mention
fact
fact
product
opinion
emotion
Example 3: Sarcastic Mention
product
brand brand
opinion service
emotion
Example 4: Mixed Mention
product
emotion service brand opinion
Example 5: Language Confusion
product
emotion service
brand opinion
fact
Example 6: Intent to Buy
product
emotion service
fact brand subject
intent
brand brand
question
The elusive hunt for binary
• For vs. Against • Like vs. Dislike • Good vs. Bad
• Ecstatic vs. Happy • Excited vs. Amused • ROFL vs. LOL
• Depressed vs. Unhappy • Sad vs. Destitute • Frustrated vs. Angry
Challenges of Automated Sentiment Analysis
§ People express opinions in complex ways
§ Cultural ideosyncracies (e.g. differences in sarcasm, irony etc)
§ The wider you throw your net and the more complex the language, the less accurate the system will be.
Agenda
1. Why Analyze Sentiment? 2. Sentiment Analysis 101 3. Practical Applications 4. Sentiment of #ThinkPH
Use Case 1: Social Focus Group
“Coffee in a can”
“Iced Coffee”
Use Case 2: Sales & Service
Use Case 3: Opinion Mining
Use Case 4: Reputation Management
Use Case 5: Consumer Insights
Use Case 6: Competitive Intelligence
Get real-time insights on your competitors
- Sun Tzu
“Know your enemy and know yourself and you can fight a
hundred battles without disaster”
What is the Sentiment of #ThinkPH? There were 4,627 mentions of #ThinkPH on 23 August 2013
What did people say about the #ThinkPH? (on a side note)
Mentions of #thinkPH Mentions of Robin Leonard + #thinkPH
Thank You!!
www.allfamous.com
Robin Leonard CEO, AllFamous Digital
robin_allfamous
robinleonard1
References
§ http://www.lct-master.org/files/MullenSentimentCourseSlides.pdf § http://www.slideshare.net/mcjenkins/how-sentiment-analysis-
works#btnNext
§ http://en.wikipedia.org/wiki/Sentiment_analysis § http://mashable.com/2010/04/19/sentiment-analysis/
§ http://www.today.mccombs.utexas.edu/2010/04/do-you-make-buying-decisions-based-on-logic-or-emotion-a-tale-of-two-chickens
§ http://adage.com/article/digital/mckinsey-finds-social-buzz-affect-sales-negatively/242039/
