Category Archives: Psychology

What traits enable crowd-workers to voluntarily disclose their identity?

Here at the World Well-Being Project, we have done many crowdsourcing experiments over the past years. Often times, we are interested not only in what the workers annotate, but also in these workers themselves. For example, in a short paper [1] we have shown that females are better and more confident than males in guessing gender from tweets, especially when it comes to guessing females.

Similarly, many surveys are done over a non-random selection of participants. This is for example a problem in exit-polls, where a non-random population agrees to share their voting preference, leading to the need for pollsters to perform corrections a posteriori. Moreover, in online studies where users are anonymous, not all will agree to disclose self-identifying or personal information. Using data from our studies on the Amazon Mechanical Turk crowdsourcing platform, we aimed to uncover which users are more likely to voluntarily disclose their identity.

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Personality Profiles of ‘Cat’ and ‘Dog People’ in Social Media

Owning a pet is very popular in the U.S. The most recent survey from the American Pet Products Association estimated that 65% of American households (79.9 million) include at least one pet. The most popular household pets are, unsurprisingly, dogs (44% of households) and cats (34.9% of households) [1].

Psychologists have long been fascinated to uncover whether individual differences drive pet ownership and preference. Most have focused on comparing the so called cat and dog people. Perhaps driven by the natures of their respective favorite pet, cat people are stereotyped as quiet, sensitive, and unorthodox while dog people are thought of as gregarious and energetic. One of the most comprehensive studies to-date [5] analysed 4,565 participants who took the Big Five personality Inventory and self-identified as dog people, cat people, both or neither. They found that dog people are higher in extraversion, agreeableness and conscientiousness and lower in neuroticism and openness, even when controlling for gender differences. Contrary to these findings, some failed to uncover differences between the two types [9] or suggested the labels do little more than offer a different way of saying masculine and feminine [11].

To shed new light on this debate, we analysed two different online behaviors using big data from social media:

  1. Mentioning animal names in Facebook posts;
  2. Using a profile picture featuring cat or a dog on Twitter.

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Sentiment, intensity and user attributes

One of the most hyped applications of big data analysis to social media is sentiment analysis (a.k.a. opinion mining). Sentiment analysis is the area of Natural Language Processing that aims to identify and extract subjective information from text. This generally includes identifying if a piece of text is subjective or objective, what sentiment (a.k.a. valence) it expresses (positive or negative), what emotion it conveys and towards which entity or aspect of the text. Companies and marketers are mostly interested in automatically inferring public opinion about products, movies or actions.

Opposite to mining these attitudes towards other objects, people also express their own emotions online. We decided to analyze this less popular facet: learning about the emotions of people posting subjective messages. In this post I’ll present variations in sentiment and intensity of Facebook posts and how these vary with the attributes of the people that post them. I will investigate a number of user traits such as gender, age and personality.

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Presentation of Self in Social Media

We study social media with the assumption that people reveal “who they are” when they post to Facebook, Twitter or Instagram: that men write more like men than women do, that extraverts look extraverted, depressed people depressed, and happy people happy. But do people present their “true selves” on Facebook and Twitter?

Of course not. Twelve year olds pretend to be thirteen — otherwise they are kicked off. And people don’t always share their embarrassing medical conditions or their illicit drug use–although they do share both surprisingly often.

Of course people want to look good. It is claimed that on dating sites like OKCupid, people on average inflate their height by two inches and their income by 20%. And, of course, they pick attractive — and sometime out of date — photos of themselves. Narcissists, on average post more photos of themselves to Facebook and edit them more often than the rest of us.

In fact, it’s not clear if people ever present their true selves–or have true selves to present. You don’t need to be a psychologist to know that simple questions like: “Are you a racist?” “Do you think I’m fat?” or even “How old are you?” do not always elicit honest answers. Sociologist Irving Goffman in his book The presentation of self in everyday life famously observed that we are always acting: when a waiter comes out of the door from the kitchen into the dining room, he puts on a persona for the diners, but when he goes back into the kitchen he doesn’t become ‘his true self’ — he just shows a different persona for the kitchen staff. We all behave differently with our friends than with our colleagues or parents. We’re always presenting ourselves on some stage.

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Differential Language Analysis for Construct Validation: Do People Differ by Astrological Sign?

Many Americans find astrology quite convincing. In fact, approximately 25% of Americans believe in Astrology, 55% of 18 to 24 year olds think astrology is at least “sort of scientific”, and a Huffington Post article on the Zodiac signs of world leaders, just released, has already accrued thousands of Facebook likes. My colleague Daniel Preotiuc-Pietro recently examined stereotypical words that accompany these beliefs by analyzing the content of tweets containing astrological sign hashtags. For example, my star sign, #leo, was most distinguished by words like “loyal”, “dynamic”, “stubborn”, “generous”, and “affectionate”. However, do leos actually differ in this way? Do people differ by their star sign at all?

I started investigating this question back in 2012 while working on what eventually became our first PLOS ONE paper: Personality, Gender, and Age in the Language of Social Media. My collaborators and I were thinking of applications for differential language analysis (DLA), our method which finds language features (e.g. words or phrases) that distinguish psychological and other human attributes. The suggestion was made that DLA could be used for psychological construct validation (i.e. does the language emerging from DLA fit the theory of the construct? How many language features, total, emerge as significantly correlated? For example, do leos use words indicating they are more stubborn or generous? How many words correlate with being a leo?).

Astrological (Zodiac) signs are a great way to prototype DLA for construct validation. Such signs seem to correspond with enduring traits that distinguish people. To believers, such signs are akin to a non-evidence-based Big 5 Personality Model, the most widely used model in Psychology. The Universal Psychic Guild represents this position:

The signs of the Zodiac can give us great insights into our day to day living as well as the many talents and special qualities we posses.

Daniel showed that differences clearly exist in descriptions of star signs. Here, we investigate whether differences clearly exist between people according to their star signs.

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Assessing the assessment: Measuring personality with Facebook status messages

What do our Facebook posts really say about us? Some dismiss them as just noise, but several research teams are seriously considering social media as a source of psychological data. A common goal of this work is to discover faster or cheaper ways to measure important but elusive variables, like personality, health, and happiness. At the World Well-Being Project, we focus on turning the language from social media into useful new measures.

For example, in a study published last year in PLoS ONE, we searched for traces of age, gender, and personality in a massive amount of social media language: 20 million status updates from 75,000 Facebook users. We found that users’ personality traits could be accurately predicted using only the words in their Facebook status updates. This is consistent with several recent studies [1-6] that suggest that statistical algorithms are surprisingly good at profiling our personalities, especially when they are fed psychologically-rich information like the structure of our Facebook social network or our Facebook likes.

Does this mean that algorithms will replace personality questionnaires?

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