The Science behind the Watson Tone Analyzer and Demo (Technical Meetup)

Wonder how your message might be perceived by the end user? Perhaps a bit too angry in your emails? Tone Analyzer can help. The IBM Watson™ Tone Analyzer Service uses linguistic analysis to detect three types of tones from text: emotion, social tendencies, and language style. Emotions identified include things like anger, fear, joy, sadness, and disgust. Identified social tendencies include things from the Big Five personality traits used by some psychologists. These include openness, conscientiousness, extroversion, agreeableness, and emotional range. Identified language styles include confident, analytical, and tentative.
Overview of the Watson™ Tone Analyzer Service
The IBM Watson™ Tone Analyzer Service uses linguistic analysis to detect three types of tones from written text: emotions, social tendencies, and writing style. Emotions identified include things like anger, fear, joy, sadness, and disgust. Identified social tendencies include things from the Big Five personality traits used by some psychologists. These include openness, conscientiousness, extraversion, agreeableness, and emotional range. Identified writing styles include confident, analytical, and tentative.
Users can input email and other written media into the Tone Analyzer service and use the results to determine if your writing comes across with the emotional impact, social tone, and writing style that you want your intended audience to see.
Tone Analyzer Service Use Cases

• Personal and business communications - Anyone could use the Tone Analyzer service to get feedback about their communications, which could improve the effectiveness of the messages and how they are received.
• Market research - Financial advisors and investors could use the Tone Analyzer service to look at the tones reflected in announcements and reports from the companies that they are researching and investing in.
• Self-branding - Bloggers and journalists could use the Tone Analyzer Service to get feedback on their tone and fine-tune their writing to reflect a specific personality or style.
• Automated contact-center agent - If a human client that is interacting with an automated call-center agent is agitated or angry, it is likely reflected in the choice of words they use to explain their problem. An automated agent could use the Tone Analyzer Service to detect those tones, and be programmed to respond to them.

Differences from sentiment and emotion analyses
The analysis performed by the Tone Analyzer service is different from sentiment and emotion analyses. Sentiment analysis can identify the positive and negative sentiments within a document or web page. The sentiments can include document-level sentiment, sentiment for a user-specified target, entity-level sentiment, and keyword-level sentiment. Emotion analysis can infer different categories of emotions such as joy, anger, disgust, sadness, and fear. The Tone Analyzer service computes emotional tones, in addition to social and writing style tones. Tone analysis is less about analyzing how someone else feels, and more about analyzing how you are coming across to others.

Presenters/BIO:
Jalal Mahmud, IBM Master Inventor, IBM Almaden Lab, San Jose.

Currently, Jalal manages personality analytics research team under IBM Watson Innovation. Jalal current research interests include social media analytics, user modeling, intelligent user experience, and machine learning. Also worked on web automation, testing, accessibility and mining.
Received his Ph.D. in Computer Science from the Department of Computer Science, State University of New York at Stony Brook in 2008. I received MS degree in Computer Science from the same department in 2006 and B.SC in CSE from Bangladesh University of Engineering and Technology (BUET). His PhD thesis was focused on developing web accessibility models from click stream analysis and machine learning.
Jalal has extensively published papers in top rated conferences and journals. Major publications are indexed by DBLP (http://www.informatik.uni-trier.de/~ley/pers/hy/m/Mahmud:Jalal.html). Received best paper nominations in top conferences such as WWW 2006, WWW 2007, IUI 2012, IUI 2013 and IUI 2014.
Regularly serves on technical program committees for major international conferences such as WWW, CIKM, IUI, ICWSM, IJCAI, ASSETS, UMAP.

Jalal has 18 issued patents, 15 other patent applications pending, and received numerous Invention Achievement Award from IBM.
Jalal's IBM Research Web page is:
http://researcher.watson.ibm.com/researcher/view.php?person=us-jumahmud

Demo: Jeancarl Bisson, Worldwide Technical Evangelist, IBM Developer Ecosystem & Startups.
JeanCarl has participated in over a hundred hackathons and found his passion of building prototypes in a matter of hours. He inspires everyone, from non-developer to advanced developer, to build their ideas via rapid prototyping methodologies and by breaking larger projects down into smaller pieces. In his spare time not building random stuff, he enjoys photography, traveling, and watching rocket launches. Follow JeanCarl at @dothewww, jeancarlbisson.com and github.com/jeancarl

DATE: August 9, 2016
LOCATION: IBM Innovation Center Silicon Valley, Foster City, CA
Agenda:
6:00 PM - 7:00 PM Networking and food/drinks
7:00 PM - 8:30 PM Presentation and demo
8:30 PM - 9:00 PM Q/A and networking