Depression Quotes Using Different Languages, This Is How To Tell! From the way you move and sleep, how you interact with the people around you, depression changes everything. This even looks at the way you speak and express yourself in writing. Sometimes this "depression language" can have a strong effect on others. Think about the impact of poetry and song lyrics Sylvia Plath and Kurt Cobain, who both committed suicide after suffering from depression.
Scientists have long tried to find a clear connection between depression and language, and technology helps us get closer to the whole picture. Our latest study, published in Clinical Psychological Science, has now revealed a group of class words that can help accurately to provide depressed quotes.
Using Different Languages
Traditionally, the linguistic analysis in this field has been carried out by researchers who read and make notes. Now, the method of text analysis with computers enables the processing of very large data banks in minutes. This can help identify linguistic traits that humans might miss, calculate the prevalence of the percentage of words and classes of words, lexical diversity, mean length of sentences, grammatical patterns, and many other metrics.
So far, personal essays and diaries by depressed people have been useful, as are the works of famous artists such as Cobain and Plath. For spoken words, pieces from the natural language of people with depression have also provided insight. When combined, findings from such research reveal tangible and consistent differences in language, between those with and without symptoms of depression.
Language can be divided into two components: content and style. Content is related to what we express - namely the meaning or point of the statement. It would surprise no one to realize that those with depressive symptoms use words that convey excessive negative emotions, especially adjectives and negative adverbs , such as "lonely", "sad", or "sad".
Language style is related to how we express ourselves, rather than the content we express. Our laboratory recently analyzed large amounts of text data in 64 online mental health forums, examining more than 6,400 members. " Absolute words" which show absolute quantities or probabilities, such as "always", "none", or "fully" are found to be better markers of mental health forums rather than pronouns and words with negative emotions.
Understanding depression languages can help us understand how people with depression think, but this also has practical implications. Researchers combine automatic text analysis with machine learning (computers that can learn from experience without being programmed) to group various mental health conditions, from natural languages to text examples such as sending blogs to depressed quotes.