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Addressing racial/ethnic inequities in vaccine hesitancy and uptake: lessons learned from the California alliance against COVID-19.
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The relationship of inner speech to executive functioning and theory of mind: An EMG study ...
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Effect of siblings on numeracy and literacy skills, and the mediating role of parental interactions in the DEPP cohort ...
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Measuring interest in early childhood – a validation of various measures of interest in young children ...
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Effect of siblings on numeracy and literacy skills, and the mediating role of parental interactions in the Elfe cohort ...
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Investigating cross situational word learning via social-communicative cues and non-social salient cues in neurotypical adults and adults with autism ...
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The Effect of Self-Distancing on Emotion Regulation and Autobiographical Remembering ...
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Finding the best way to put media bias research into practice via an annotation app ...
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Do Chimpanzees Reason According to the Disjunctive Syllogism? ...
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Semantics and interpretation of the response particles ano ‘yes’ and ne ‘no’ ...
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Labour market discrimination and biases in human judgement and Artificial Intelligence ...
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Experiment 2: Jury Suggestibility: The Effect of Judicial Instruction on Juror’s use of Covert Recording Transcripts ...
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Isolating the locus of informational interference during speech-in-noise perception: the role of temporal predictability ...
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#Bittersweet: Positive, negative, and mixed emotions in twitter posts ...
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Abstract:
We are interested in the emotions associated with feelings of bittersweet. To that end, we will use LIWC (Linguistic Inquiry and Word Count) to investigate how much positive, negative, and mixed emotion people express in tweets that include #happy, #sad, and #bittersweet. This is our first archival analysis of a corpus of words, so we have only sketched out a handful of hypotheses at this point. We will only analyze tweets from 2007 (when Twitter introduced hashtags) to 2009. There were 813 tweets with #bittersweet in that period, which will give us enough power to detect the hypothesized patterns. Based on the results of those analyses, we will file subsequent preregistrations in which we (a) clarify our hypotheses, (b) add more hypotheses, and (c) analyze tweets from 2007 through 2020. . ...
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Keyword:
Bittersweet; FOS Psychology; Mixed Emotions; Psychology; Sentiment Analyis; Social and Behavioral Sciences; Social Media Analysis; Social Psychology
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URL: https://dx.doi.org/10.17605/osf.io/5234a https://osf.io/5234a/
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Are neural language models sensitive to false belief? A computational study. ...
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Neural correlates and subjective assessments of multimodal training on perception of foreign language prosody ...
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