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Transcript of Big Data
Business & Politics
Understanding what makes something memorable
Close the engagement gap between political candidates or companies and their audience
Identify opinion leaders
What is Big Data?
*Big data is a new class of asset like currency or gold
*Big data acts as a predictor for events and trends
*Big data provides a picture of cultural norms, dialogue, trends and events that informs business, scholarship, legislation, art, eduction and so on
Big Data Tools
-Social Media Monitoring
New Areas of Study
Changes to the User's Online Experience
*Searches based on the searcher not rankings provides more relevant and intuitive web searches
*Better ways to explore and enjoy stories and memories
*Visualization of information through Infographs
*Sentiment Analysis as a standard feature on search engines
Scholarly & Cultural
Quantitative Research in the Digital Age
The Industrial Internet
Digital sensors inside
Search Engine Information
Cell Phone Data
Twitterology: The Study of Behavior and Language Via 140 Characters
Culturomics: study of the wide array of new digital phenomena spanning the social sciences and the humanities
Social Genome Mapping: mapping of users' electronic makeup and connections
Crowdsourcing: the practice of obtaining needed services, ideas, or content by soliciting contributions from online communities
Google searches predict home sales better than real estate economists
Tailored Products and Services
Real feedback-no need to speculate
Focus Groups without size limits
Cater to customer's tastes
Knowing where customers came from (websites), how they viewed your page (iPhone, computer) Customer opinions are readily available through feedback forms and discussion forums
Forecasting the impact of a newspaper's editorials on a company's stock price
Pinpoint effects of specific issues on customer perceptions to adjust marketing and public relations techniques
Small businesses can compete with those with greater resources
Predict which customers will visit again, what products interest them and what special offers will appeal to them
Ranking businesses for things like greenest, women friendly, etc.
Criticisms of Big Data
*Who is generating the information and how do they represent the total population?
*Privacy issues with conceptual, legal, and technological implications
*Words do not equal moods because of the subjective nature, subtleties, irony, slang, sarcasm, etc.
*Math models are like metaphors in that they over-simplify
*Will Big Data usher in a digital surveillance state mainly serving corporate interests? aka Is Big Data really Big Brother?
*Algorithms are too simple to apply to human behavior
*Huge data sets and fine-grained measurements increase the number of false discoveries
*Unfair or discriminatory statistical inferences may effect products, bank loans and health insurance
*When humans are overloaded with choices they tend to copy others and follow trends. Correlations do not equal causation.
*Withholding data due to competition or secrecy effect data outcomes
*Workers with a knowledge of a subject and an understanding of natural, intuitive language.
*Understanding the demographics behind content. Who uses SNS & Blogs?
*Pondering the ethical dimensions of this work rather that just the math
*Sophisticated Sentiment Analysis algorithms & human annotators to verify results
*Clean and correct data that accounts for local variations
*Privacy safeguards for corporate and personal information
*Moving older data online
Big Data Tools
Data Repositories & Marketplaces
Google Books + Magazines
Algorithms Distinguishing context of words
Windows Azure Marketplace
Bing Webmaster Tool
Data + Processing
Perform rigorous quantitative inquiries into social sciences & humanities
Trace word patterns & thematic elements in literature and media
Understanding collective memory through various perspectives
Fitness or evolutionary strength of language and ideas
Define and predict movement and social change through associated media
Looking for agenda phrases and depictions in media
Locating origins and historic parallels
Understanding the demographics of a movement
Understanding affective response