Data Skeptic10 Huhti 2015

Computer-based Personality Judgments

Guest Youyou Wu discuses the work she and her collaborators did to measure the accuracy of computer based personality judgments. Using Facebook "like" data, they found that machine learning approaches could be used to estimate user's self assessment of the "big five" personality traits: openness, agreeableness, extraversion, conscientiousness, and neuroticism. Interestingly, the computer-based assessments outperformed some of the assessments of certain groups of human beings. Listen to the episode to learn more.

The original paper Computer-based personality judgements are more accurate than those made by humansappeared in the January 2015 volume of the Proceedings of the National Academy of Sciences (PNAS).

For her benevolent Youyou recommends Private traits and attributes are predictable from digital records of human behavior by Michal Kosinski, David Stillwell, and Thore Graepel. It's a similar paper by her co-authors which looks at demographic traits rather than personality traits.

And for her self-serving recommendation, Youyou has a link that I'm very excited about. You can visitApplyMagicSauce.com to see how this model evaluates your personality based on your Facebook like information. I'd love it if listeners participated in this research and shared your perspective on the results via The Data Skeptic Podcast Facebook page. I'm going to be posting mine there for everyone to see.

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(601)

Streetlight Outage and Crime Rate Analysis with Zach Seeskin

This episode features a discussion with statistics PhD student Zach Seeskin about a project he was involved in as part of the Eric and Wendy Schmidt Data Science for Social Good Summer Fellowship. Th...

18 Heinä 201433min

[MINI] Experimental Design

This episode loosely explores the topic of Experimental Design including hypothesis testing, the importance of statistical tests, and an everyday and business example.

11 Heinä 201415min

The Right (big data) Tool for the Job with Jay Shankar

In this week's episode, we discuss applied solutions to big data problem with big data engineer Jay Shankar. The episode explores approaches and design philosophy to solving real world big data busin...

7 Heinä 201449min

[MINI] Bayesian Updating

In this minisode, we discuss Bayesian Updating - the process by which one can calculate the most likely hypothesis might be true given one's older / prior belief and all new evidence.

27 Kesä 201411min

Personalized Medicine with Niki Athanasiadou

In the second full length episode of the podcast, we discuss the current state of personalized medicine and the advancements in genetics that have made it possible.

20 Kesä 201457min

[MINI] p-values

In this mini, we discuss p-values and their use in hypothesis testing, in the context of an hypothetical experiment on plant flowering, and end with a reference to the Particle Fever documentary and h...

13 Kesä 201416min

Advertising Attribution with Nathan Janos

A conversation with Convertro's Nathan Janos about methodologies used to help advertisers understand the affect each of their marketing efforts (print, SEM, display, skywriting, etc.) contributes to t...

6 Kesä 20141h 16min