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		114.51
Past tense	You tend to talk about the past.	66.78
Space		25.54
Occupation & work	You talk a lot about jobs and your work.	24.56
Positive Feelings	You often discuss positive sensations and feelings.	19.67
Similes		18.93
Cognitive processes	You often talk about various cognitive processes like learning, thinking, knowing, etc.	15.2
Certainty		14.18
Sleep		12.56
Insight		6.7
Motion		5.9

Primordial, Conceptual and Emotional Content

Feature	Description	Score
Temporal References		76.93
Social behavior		62.07
Abstract thought		51.74
Affection		22.46
Glory		19.62
Positive affect		12.27
Moral imperative		10.49
Anxiety		5.37

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
	music	27	794	Tweet @music
	mvolpe	4008	9740	Tweet @mvolpe
	jenny8lee	1946	5349	Tweet @jenny8lee
	tedchris	959	329967	Tweet @tedchris
	tibbon	8653	2208	Tweet @tibbon

Created by Dan Zarrella © 2009 (70,629 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