Sliding into happiness: A new tool for measuring affective responses to words.

Reliable measurement of affective responses is critical for research into human emotion. Affective evaluation of words is most commonly gauged on multiple dimensions-including valence (positivity) and arousal-using a rating scale. Despite its popularity, this scale is open to criticism: It generates ordinal data that is often misinterpreted as interval, it does not provide the fine resolution that is essential by recent theoretical accounts of emotion, and its extremes may not be properly calibrated. In 5 experiments, the authors introduce a new slider tool for affective evaluation of words on a continuous, well-calibrated and high-resolution scale. In Experiment 1, participants were shown a word and asked to move a manikin representing themselves closer to or farther away from the word. The manikin's distance from the word strongly correlated with the word's valence. In Experiment 2, individual differences in shyness and sociability elicited reliable differences in distance from the words. Experiment 3 validated the results of Experiments 1 and 2 using a demographically more diverse population of responders. Finally, Experiment 4 (along with Experiment 2) suggested that task demand is not a potential cause for scale recalibration. In Experiment 5, men and women placed a manikin closer or farther from words that showed sex differences in valence, highlighting the sensitivity of this measure to group differences. These findings shed a new light on interactions among affect, language, and individual differences, and demonstrate the utility of a new tool for measuring word affect. (PsycINFO Database Record

Affective biases in English are bi-dimensional.

A long-standing observation about the interface between emotion and language is that positive words are used more frequently than negative ones, leading to the Pollyanna hypothesis which alleges a predominantly optimistic outlook in humans. This paper uses the largest available collection of affective ratings as well as insights from linguistics to revisit the Pollyanna hypothesis as it relates to two dimensions of emotion: valence (pleasantness) and arousal (intensity). We identified systematic patterns in the distribution of words over a bi-dimensional affective space, which (1) run counter to and supersede most prior accounts, and (2) differ drastically between word types (unique, distinct words in the lexicon) and word tokens (number of occurrences of available words in the lexicon). We argue for two factors that shape affect in language and society: a pro-social benevolent communication strategy with its emphasis on useful and dangerous phenomena, and the structure of human subjective perception of affect.

Emotion and language: valence and arousal affect word recognition.

Emotion influences most aspects of cognition and behavior, but emotional factors are conspicuously absent from current models of word recognition. The influence of emotion on word recognition has mostly been reported in prior studies on the automatic vigilance for negative stimuli, but the precise nature of this relationship is unclear. Various models of automatic vigilance have claimed that the effect of valence on response times is categorical, an inverted U, or interactive with arousal. In the present study, we used a sample of 12,658 words and included many lexical and semantic control factors to determine the precise nature of the effects of arousal and valence on word recognition. Converging empirical patterns observed in word-level and trial-level data from lexical decision and naming indicate that valence and arousal exert independent monotonic effects: Negative words are recognized more slowly than positive words, and arousing words are recognized more slowly than calming words. Valence explained about 2% of the variance in word recognition latencies, whereas the effect of arousal was smaller. Valence and arousal do not interact, but both interact with word frequency, such that valence and arousal exert larger effects among low-frequency words than among high-frequency words. These results necessitate a new model of affective word processing whereby the degree of negativity monotonically and independently predicts the speed of responding. This research also demonstrates that incorporating emotional factors, especially valence, improves the performance of models of word recognition.

Concreteness ratings for 40 thousand generally known English word lemmas.

Concreteness ratings are presented for 37,058 English words and 2,896 two-word expressions (such as zebra crossing and zoom in), obtained from over 4,000 participants by means of a norming study using Internet crowdsourcing for data collection. Although the instructions stressed that the assessment of word concreteness would be based on experiences involving all senses and motor responses, a comparison with the existing concreteness norms indicates that participants, as before, largely focused on visual and haptic experiences. The reported data set is a subset of a comprehensive list of English lemmas and contains all lemmas known by at least 85 % of the raters. It can be used in future research as a reference list of generally known English lemmas.

Norms of valence, arousal, and dominance for 13,915 English lemmas.

Information about the affective meanings of words is used by researchers working on emotions and moods, word recognition and memory, and text-based sentiment analysis. Three components of emotions are traditionally distinguished: valence (the pleasantness of a stimulus), arousal (the intensity of emotion provoked by a stimulus), and dominance (the degree of control exerted by a stimulus). Thus far, nearly all research has been based on the ANEW norms collected by Bradley and Lang (1999) for 1,034 words. We extended that database to nearly 14,000 English lemmas, providing researchers with a much richer source of information, including gender, age, and educational differences in emotion norms. As an example of the new possibilities, we included stimuli from nearly all of the category norms (e.g., types of diseases, occupations, and taboo words) collected by Van Overschelde, Rawson, and Dunlosky (Journal of Memory and Language 50:289-335, 2004), making it possible to include affect in studies of semantic memory.

Splitting of the Mind: When the You I Talk to is Me and Needs Commands.

Self-talk has fascinated scholars for decades but has received little systematic research attention. Three studies examined the conditions under which people talk to themselves as if they are another person, indicating a splitting or fragmentation of the self. Fragmented self-talk, defined by the use of the second person, You, and the imperative, was specifically expected to arise in contexts requiring explicit self-control. Results showed that fragmented self-talk was most prevalent in response to situations requiring direct behavior regulation, such as negative events (Study 1), experiences of autonomy (Study 2), and action as opposed to behavior preparation or behavior evaluation (Study 3). Therefore, people refer to themselves as You and command themselves as if they are another person in situations requiring conscious self-guidance. The implications of these findings for behavior change are discussed.

Learning to fail: reoccurring tip-of-the-tongue states.

This experiment looked at elicited tip-of-the-tongue (TOT) states to test the hypothesis that making an error once makes people more likely to make it again, via an implicit learning mechanism. We present a methodology that allows us to determine whether error reoccurrences are due to error learning or to the fact that some items tend to pose repeated difficulty to participants. We elicited TOTs by asking participants to supply the word that fitted a given definition. Each time participants indicated that they were experiencing a TOT they were randomly assigned a delay of either 10 or 30 seconds, during which they were asked to keep trying to retrieve the item. After the delay, the correct answer was supplied. We argue that this longer delay in a TOT state amounts to greater implicit learning of the erroneous state. A period of 48 hours later, participants returned to the laboratory and were asked to supply the words for the same definitions as those seen on Day 1. Results showed that TOTs were almost twice as likely to reoccur on words that had elicited a TOT and been followed by a long delay than on those that had been followed by a short delay.