Neural NetworksOriginally sought to reproduce the waythe nervous system works.Had the ability to learn complexrelationships with any assumptions.Can learn complex non linearrelationships.
Biological metaphor: encode problems as chromosomes.Fitness function.Evolve different mapping functions via principles of evolution.Cross over and mutation (note: mutation rates not as powerful asyou may think...)MR example: used GA’s to evolve panel sample balancing - rim balancing.
Social Media Data• We have a lot of text...that we didn’t have before...• Text has its own set of problems..unlike Gore Vidal we don’t speak in sentences.• “#itsucks phat”• Txt messages, social media messages.• Parsing and tokenizing
Sentiment Analysis• One of the frontiers for MR and Big Data• Can we tell the sentiment behind the comment ?• Text is messy because language is messy. • Grammatical vs Stochastic
Surveys, Market Research and Big Data• Fusion of data• Survey and behavioral• “Whole respondent” view• Surveys can be “big data”
Prediction and Market Research • Statisticians are the new “rock stars” (Eric Schmidt) • MR has to embrace prediction and realize the limits of explanation. It’s great to know why, better to know what’s next ? • Theories of respondents and consumers...