TweetPsych uses two linguistic analysis algorithms (RID and LIWC) to build a psychological profile of a person based on the content of their tweets. The service analyzes your last 1000 tweets and works best on users who have posted more than 1000 updates. It also works best on accounts that are operated by a single user and use Twitter in a conversational manner, rather than simply a content distribution platform. For more information read the blog post or follow the creator Dan Zarrella

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The features displayed below are those for which you score higher than the average. The score indicates how much more often you tweeted something that matched each feature than the baseline.

Cognitive Content

Feature	Description	Score
Time		64.77
Similes		33.66
Cognitive processes	You often talk about various cognitive processes like learning, thinking, knowing, etc.	16.28
Leisure		14.53
Past tense	You tend to talk about the past.	9.87
Occupation & work	You talk a lot about jobs and your work.	8.86
Motion		7.33
Inhib		5.45

Primordial, Conceptual and Emotional Content

Feature	Description	Score
Abstract thought		32.61
Temporal References		30.98
Affection		19.54
Moral imperative		14.34

The users below are those users who are the closest match to your TweetPsych profile. As we profile more users this will get more accurate.

Some people that think like you:		Tweets	Followers
	feliciaday	2389	777281	Tweet @feliciaday
	nickzdon	232	27	Tweet @nickzdon
	rowanoulton	435	74	Tweet @rowanoulton
	hugovega	309	82	Tweet @hugovega
	keshav	9972	668	Tweet @keshav

Created by Dan Zarrella © 2009 (67,543 accounts analyzed)



The results presented here are for entertainment purposes only and the terms used are psychological and may not equate with their normal, english language usage