The words you use can reveal a lot about your personality, and in more subtle ways than you think. Researchers (like me) are using that fact to look at what you do online and discover the secrets of your personality without you even knowing. Most of our tools are for research-use only right now, but in this post, I will introduce you to one that's online and ready to be tried.

First - a very quick bit of background on psycholinguistics and computational linguistics. Research has shown that words called particles, which include pronouns (you, I, we), prepositions, articles, and auxiliary verbs (could, should, may), are inexorably linked to a person's personality, emotional state, and social identity [1].

These words can be grouped into categories, and by analyzing people's writing or speech, we can find connections between categories of words and individual traits. We can even write computer programs to do this. We start with a long list of words and the category for each word, and then feed in a text document. The program compares it to the lists of words and outputs a report. The results of that report can then be used in statistical analysis to find connections between word use and personal attributes.

Some examples? As people get older, they tend to use more positive emotion words, more future tense verbs, and fewer past tense verbs. Men tend to curse far more than women. Looking at Big Five personality traits, people who rate higher in neuroticism (indicating they are less emotionally stable) tend to use more anxiety words (like "worry"). Agreeable people tend to use more positive emotion words. People who are anxious use more explainer words (like "because" and "since").

The list goes on and on. Finding these relationships has become a popular area of research.

These insights have become especially powerful in the age of social media. In my lab and others, we have used this kind of text analysis to study what people post on Facebook, Twitter, and other sites. It has been used to predict social media users' Big Five Personality traits [2] and the strength of their interpersonal relationships [3] among other factors. 

Most of the computer programs that discover people's personality traits from social media are locked away in researchers' labs, making it hard for you to see what these algorithms can discover about you. But fear not - there is one online tool you can use to analyze your Twitter personality right now.

It's called Analyze Words, and you can find it at http://analyzewords.com. Enter your (or anyone else's) Twitter handle, and see a report of some high-level personality traits. As an example, here's an analysis of my own Twitter account from the site:

 A few things to keep in mind if you do this analysis. First, we often present ourselves in a careful way online. These results are an analysis of that personality, not necessarily of our internal, personal selves. I have a few other Twitter accounts that look quite different (try my dog's Twitter handle @hopper_dog for comparison - I write text for both accounts, but the style is quite different). Also, your results may change over time. Depending on the type of thing you happen to be tweeting, you may see big differences. This can be especially true if you are tweeting at or about an event and then go back to "normal" tweeting behavior.

This is my first blog post for Psychology Today, and if you come back, you'll find me posting a lot about the kinds of things - especially hidden or implicit traits - we can find out about you by analyzing your social media presence. It's my area of research, and it is fascinating, but it is wrapped up with major ethical questions that present their own intellectual challenge. We'll tackle all of those issues here, and if you have specific questions you'd like me to address, please leave me a suggestion in the comments!

[1] Pennebaker, James W., Matthias R. Mehl, and Kate G. Niederhoffer. "Psychological aspects of natural language use: Our words, our selves." Annual review of psychology 54.1 (2003): 547-577.

[2] Golbeck, J., Robles, C., Edmondson, M., & Turner, K. (2011, October). Predicting personality from twitter. In Privacy, security, risk and trust (passat), 2011 ieee third international conference on and 2011 ieee third international conference on social computing (socialcom) (pp. 149-156). IEEE.

[3] Gilbert, E., & Karahalios, K. (2009, April). Predicting tie strength with social media. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 211-220). ACM.

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