article_snippet: Whether you use it to share news and emotions, or to complain about brands, what you write on Twitter may say more about you than you think.
article_snippet: Users who are most upbeat use lots of positive words and 'we' when they tweet, whereas the tweets of people who are predominantly worried contain anxious words and nervous questions.
article_snippet: Users who are most upbeat use lots of positive words and 'we' when they tweet.
article_snippet: Tweets by worried users are dominated by anxious words and nervous questions.
article_snippet: Angry Twitter users say 'you' a lot and write in capitals.
article_snippet: Angry Twitter users say 'you' a lot and write in capitals and people who have a high depression score make lots of self-references and tend to be inward-looking, the tool says.
article_snippet: Plugged in' tweeters are socially engaged and use social words as well as talking to specific friends, according to the tool.
article_snippet: Twitter users who score highly in being a 'spacy valley girl' are excitable and have a habit of tweeting LOLLLLLs, the tool says.
article_snippet: Users who are most upbeat use lots of positive words and 'we' when user's thinking styles tweet, whereas angry Twitter users say 'you' a lot and write in capitals, while depressed people make lots of self-references and tend to be inward-looking, the tool says.
article_snippet: A study by psychologists at the University of Pennsylvania last month revealed that words used in social media profiles can help determine parts of the US that are more likely to have high numbers of deaths due to heart disease.
article_snippet: Psychologist Johannes Eichstaedt led a team that analysed 826million tweets from 1,400 counties in the US for words associated with anger, anxiety and other emotions, to emotionally profile users.
article_snippet: a team that analysed 826million tweets from 1,400 counties in the US for words associated with anger, anxiety and other emotions, to emotionally profile users found that counties where people’s tweets included hostile, aggressive and lazy words, such as ‘jealous’ and ‘bored’ had higher rates of death from heart attacks and strokes, whereas places with more positive tweeters had less.
article_snippet: This suggests that negative and angry language used on social media could be used to predict medical conditions, but the field of research is young.