Emotion Measurement and Statistical Analysis in Leiden

Emotion Measurement and Statistical Analysis.
Leiden, The Netherlands, October 31 – November 1, 2017
Dr. Herb Meiselman & Anne Hasted 

Course Fee US$ 1,595
Register by October 31st to get a discounted rate of US$ 1,495

To register, please email herb@herbmeiselman.com

This course combines information on how to measure emotions and how to analyze the measurement data, using state of the art techniques for both the measurement phase and the analysis phase.

  

  1. Introduction and Emotions (Definitions) – HLM
  • Definitions of emotions
  • Emotion and mood
  • Emotion theories and primary emotions
  • Positive and negative emotions
  • Disgust

 

  1. Designing Emotion Questionnaires.

 

Emotion Lists – HLM

  • Using words in emotion research
  • Using images in emotion research
  • Using faces in emotion research
  • Using film clips in emotion research
  • Criteria for emotion lists

Aspects of Questionnaire Layout – AH

  • Randomisation of emotion lists
  • CATA lists – layout
  • CATA  – what is (and is not) CATA measuring
  • RATA- is it worth the effort?
  • Results from some of the Ares/Jaeger papers (Eye Tracking)

 

  1. Traditional Questionnaires – HLM
  • Good sources of emotion terms
  • POMS – Profile of Mood States
  • MAACL-R – Mood Affective Adjective Check List
  • PANAS – Positive Affect Negative Affect Schedule

 

  1. Testing for Differences Between Products – AH
  • Comparison of attribute and CATA scales from a statistical viewpoint
  • Analysis of scale data – is ANOVA OK?  Non parametric alternatives.
  • Analysis of CATA data – two products and multi products
  • Multiple comparisons (within and between emotions)

 

  1. Body Responses – HLM
  • Skeletal muscle movements (mainly facial
  • Vocalizations
  • Postures
  • Gestures
  • Physiological responses

 

  1. Sentiment Analysis

Sentiment analysis – HLM

  • Sentiment analysis definition
  • Sentiment analysis from text
  • Challenges for Sentiment Analysis
  • Lexicons

Statistical Analysis of Text Data  – AH

  • Statistical analysis of data – software solutions Twitter R

 

  1. Product Applications – HLM
  • Senso-Emotional Optimization from MMR Research Worldwide
  • Geneva Emotion and Odor Scale (GEOS), ScentMoveTM and UniGEOS from Firmenich and University of  Geneva
  • Adriant’s Sense’n FeelTM Emotion Boards
  • EsSense ProfileR   and EsSense25 from McCormick
  • EmoSemio (from Italy)
  • The EmoSensory® Wheel
  • Wine Emotions (from Italy)
  • Wine Emotions (from Australia)
  • Beverages (Global)
  • TDS/TDE

 

  1. Investigating Interrelationships Between Emotion Scores – AH
  • Within and between product correlations.
  • Principal component Analysis/Factor Analysis
  • Overlaying Liking

 

  1. Best Worst Scaling Methodology & Analysis – AH
  • Short practical exercise
  • Analysis of data – simple counting.
  • Conditional logistic regression (XLSTAT) – interpretation of model results

 

  1. Cross Cultural Testing of Emotions. 

Cross cultural – HLM

  • Cultural variation
  • Defining culture
  • Anglocentrism
  • Language and translation
  • Examples of cross cultural studies

Visualising and Testing Cross Cultural Interactions – AH

  • Visualising and testing cross cultural interactions
  • Analysis of Variance
  • Correspondence Analysis

 

 

 

 

THE INSTRUCTORS

herb125 Herb Meiselman has lectured and consulted on consumer research methods for the past 15 years. An internationally known expert in the fields of sensory and consumer research, product development, and food service system design and evaluation, he has served as Editor of several research journals, including Food Quality and Preference and Journal of Foodservice. He has held Visiting Professorships at both Reading University and Bournemouth University, UK, and Orebro University, Sweden.  He is currently President of the Research Committee of the Institut Paul Bocuse, Lyon, France. Herb worked at Natick Laboratories on product development and consumer product research for over 30 years.

 

Anne Hasted started her career as an academic statistician in the Department of Applied Statistics at the University of Reading, leaving to set up Qi Statistics in 1989. She has a broad range of experience in industry (particularly in food, petrochemicals and packaging) and is a recognised expert on applications of statistical methods in the field of sensory and consumer research. She is co-developer with Hal Macfie of a successful programme of “hands on” training courses for sensory and consumer researchers which are recognised worldwide.