Sentiment Analysis and Applications in the News and Media Industry

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This is the talk I gave to the Financial Times on 12 September 2013 on Sentiment Analysis and applications in the news and media industry.

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Robin Leonard CEO, AllFamous Digital

robin_allfamous

robinleonard1

SENTIMENT ANALYSIS and applications in the news and media industry

What is the ROI of your mother?

http://www.youtube.com/watch?v=xZY5b85KoOU

Agenda

1.  Why Analyze Sentiment? 2.  Sentiment Analysis 101 3.  Practical Applications

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

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

Use Case 1: Get to the heart of the News

In real time listen for spikes in mention volumes to identify the latest news stories

Use Case 2: Faster Content Crowdsourcing

Once there is a breaking story, quickly identify all the images, videos and public

created content on a topic

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”

Use Case 7: Brand Monitoring

Social Media sentiment is the #nofilter voice of the people

Conclusion

Are you listening?

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/

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