Emotions explain differences in the diffusion of true vs. false social media rumors
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ABSTRACT:
SUBMITTER: Prollochs N
PROVIDER: S-EPMC8608927 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPublic interest in radiation rose after the Tokyo Electric Power Company (TEPCO) Fukushima Daiichi Nuclear Power Station accident was caused by an earthquake off the Pacific coast of Tohoku on March 11, 2011. Various reports on the accident and radiation were spread by the mass media, and people displayed their emotional reactions, which were thought to be related to information about the Fukushima accident, on Twitter, Facebook, and other social networking sites. Fears about radiation were spread as well, leading to harmful rumors about Fukushima and the refusal to test children for radiation. It is believed that identifying the process by which people emotionally responded to this information, and hence became gripped by an increased aversion to Fukushima, might be useful in risk communication when similar disasters and accidents occur in the future. There are few studies surveying how people feel about radiation in Fukushima and other regions in an unbiased form.ObjectiveThe purpose of this study is to identify how the feelings of local residents toward radiation changed according to Twitter.MethodsWe used approximately 19 million tweets in Japanese containing the words "radiation" (), "radioactivity" (), and "radioactive substances" () that were posted to Twitter over a 1-year period following the Fukushima nuclear accident. We used regional identifiers contained in tweets (ie, nouns, proper nouns, place names, postal codes, and telephone numbers) to categorize them according to their prefecture, and then analyzed the feelings toward those prefectures from the semantic orientation of the words contained in individual tweets (ie, positive impressions or negative impressions).ResultsTweets about radiation increased soon after the earthquake and then decreased, and feelings about radiation trended positively. We determined that, on average, tweets associating Fukushima Prefecture with radiation show more positive feelings than those about other prefectures, but have trended negatively over time. We also found that as other tweets have trended positively, only bots and retweets about Fukushima Prefecture have trended negatively.ConclusionsThe number of tweets about radiation has decreased overall, and feelings about radiation have trended positively. However, the fact that tweets about Fukushima Prefecture trended negatively, despite decreasing in percentage, suggests that negative feelings toward Fukushima Prefecture have become more extreme. We found that while the bots and retweets that were not about Fukushima Prefecture gradually trended toward positive feelings, the bots and retweets about Fukushima Prefecture trended toward negative feelings.
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Project description:Measuring sentiment in social media text has become an important practice in studying emotions at the macroscopic level. However, this approach can suffer from methodological issues like sampling biases and measurement errors. To date, it has not been validated if social media sentiment can actually measure the temporal dynamics of mood and emotions aggregated at the level of communities. We ran a large-scale survey at an online newspaper to gather daily mood self-reports from its users, and compare these with aggregated results of sentiment analysis of user discussions. We find strong correlations between text analysis results and levels of self-reported mood, as well as between inter-day changes of both measurements. We replicate these results using sentiment data from Twitter. We show that a combination of supervised text analysis methods based on novel deep learning architectures and unsupervised dictionary-based methods have high agreement with the time series of aggregated mood measured with self-reports. Our findings indicate that macro level dynamics of mood expressed on an online platform can be tracked with social media text, especially in situations of high mood variability.
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Project description:False political information-misinformation or disinformation-is widely spread on social media. Individual social media users play a large part in this. However, only a minority actively share false material. It is important to establish what sets these individuals apart from those who do not, and why they do it. Motivations for sharing may vary and are likely to differ between people who share false material unknowingly and on purpose. In this paper we consider the extent to which individual differences in personality and other variables, and motivations for sharing, are associated with the likelihood of people sharing false political information both accidentally and deliberately. In a series of four studies (Ns = 614, 563, 627, 113) we examined predictors of sharing false political information using different methodological approaches. Across the four studies, a key finding was that positive schizotypy is associated with measures of sharing false information both accidentally and deliberately. Motivations for sharing political information online were also relevant, with sharing for reasons of 'raising awareness' appearing particularly important. Implications for research and practice are discussed.
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Project description:Computer-mediated communication is driving fundamental changes in the nature of written language. We investigate these changes by statistical analysis of a dataset comprising 107 million Twitter messages (authored by 2.7 million unique user accounts). Using a latent vector autoregressive model to aggregate across thousands of words, we identify high-level patterns in diffusion of linguistic change over the United States. Our model is robust to unpredictable changes in Twitter's sampling rate, and provides a probabilistic characterization of the relationship of macro-scale linguistic influence to a set of demographic and geographic predictors. The results of this analysis offer support for prior arguments that focus on geographical proximity and population size. However, demographic similarity - especially with regard to race - plays an even more central role, as cities with similar racial demographics are far more likely to share linguistic influence. Rather than moving towards a single unified "netspeak" dialect, language evolution in computer-mediated communication reproduces existing fault lines in spoken American English.
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Project description:A feared complication of acute myocardial infarction is the formation of a cardiac pseudoaneurysm. We report a case of a gargantuan, arrhythmogenic left-ventricular pseudoaneurysm with contradictory morphological characteristics. The integrative use of high-resolution 3-dimensional magnetic resonance imaging and computed tomography proved essential for the diagnostic discrimination and successful therapeutic intervention. (Level of Difficulty: Advanced.).
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Project description:Exposure to acute stress induces multiple emotional responses, each with their own unique temporal dynamics. Dynamic functional connectivity (dFC) measures the temporal variability of network synchrony and captures individual differences in network neurodynamics. This study investigated the relationship between dFC and individual differences in emotions induced by an acute psychosocial stressor. Sixteen healthy adult women underwent fMRI scanning during a social evaluative threat (SET) task, and retrospectively completed questionnaires that assessed individual differences in subjectively experienced positive and negative emotions about stress and stress relief during the task. Group dFC was decomposed with parallel factor analysis (PARAFAC) into 10 components, each with a temporal signature, spatial network of functionally connected regions, and vector of participant loadings that captures individual differences in dFC. Participant loadings of two networks were positively correlated with stress-related emotions, indicating the existence of networks for positive and negative emotions. The emotion-related networks involved the ventromedial prefrontal cortex, cingulate cortex, anterior insula, and amygdala, among other distributed brain regions, and time signatures for these emotion-related networks were uncorrelated. These findings demonstrate that individual differences in stress-induced positive and negative emotions are each uniquely associated with large-scale brain networks, and suggest that dFC is a mechanism that generates individual differences in the emotional components of the stress response. Hum Brain Mapp 38:6185-6205, 2017. © 2017 Wiley Periodicals, Inc.
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Project description:Previous studies on the neurocognitive impact of cannabis use have found working and declarative memory deficits that tend to normalize with abstinence. An unexplored aspect of cognitive function in chronic cannabis users is the ability to distinguish between veridical and illusory memories, a crucial aspect of reality monitoring that relies on adequate memory function and cognitive control. Using functional magnetic resonance imaging, we show that abstinent cannabis users have an increased susceptibility to false memories, failing to identify lure stimuli as events that never occurred. In addition to impaired performance, cannabis users display reduced activation in areas associated with memory processing within the lateral and medial temporal lobe (MTL), and in parietal and frontal brain regions involved in attention and performance monitoring. Furthermore, cannabis consumption was inversely correlated with MTL activity, suggesting that the drug is especially detrimental to the episodic aspects of memory. These findings indicate that cannabis users have an increased susceptibility to memory distortions even when abstinent and drug-free, suggesting a long-lasting compromise of memory and cognitive control mechanisms involved in reality monitoring.
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Project description:To investigate whether people can implicitly learn regularities in a social context, we developed a new implicit sequence learning task combining elements from classic false belief and serial reaction time tasks. Participants learned that protagonists were offered flowers at four locations. The protagonists' beliefs concerning the flowers were true or false, depending on their orientation, respectively, toward the scene (so that the flowers could be seen) or away from it. Unbeknown to the participants, there was a fixed belief-related sequence involving three dimensions (identity of the two protagonists, true-false belief orientation held by the protagonists, and flower location as believed by the protagonists). Participants had to indicate as fast as possible where the flowers were located (Experiment 1), or how many flowers were given (Experiment 2) according to the protagonists. Experiment 1 combined perceptual and motor processes (as both the belief-related sequence and motor responses referred to location), whereas Experiment 2 unconfounded the sequence and motor responses, allowing to investigate pure perceptual implicit learning. For reasons of comparison, two non-social conditions were created in Experiment 2 by replacing the protagonists with two non-social objects-colored cameras or shapes. Results revealed significant implicit sequence learning of all belief-related dimensions in Experiment 1, and of true-false belief orientation in Experiment 2, even without a motor confound. Importantly, there were faster reaction times and stronger sequence learning effects in the social than in the non-social conditions. The present findings demonstrate for the first time that people are able to implicitly learn belief-related sequences.
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Project description:Memory is reconstructive and error-prone, which make memory illusions very common in everyday life. However, studying memory illusions can provide valuable insights into how memory works. Pupil response has emerged, in recent years, as an indicator of memory encoding and retrieval, however its validity as a measure of memory success is debated. In this study, we explored whether pupil response patterns can differentiate true from false memories and whether variations in the temporal dynamics of pupil response can elucidate the mechanisms underlying false memory creation. The Deese-Roediger-McDermott (DRM) paradigm was employed to generate false memories in two separate experiments involving visual and auditory stimuli. Pupil responses effectively differentiated true from false memories based on variations in pupil amplitude at different temporal components. This discrimination remained consistent across both experiments, with slightly stronger effects in the auditory condition, aligning with the more pronounced false memory effects in this condition. Notably, differential pupil responses between true and false memories varied based on the type of memory involved at recognition. These findings provide valuable insights into the cognitive processes underlying memory distortions, with implications for theoretical frameworks and real-world contexts.
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