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25 results for “data narratives”
DIPROMATS 2024 - Shared Task 2: testing data for narrative identification
<p>Narratives are causally connected sequences of events that are selected and evaluated as meaningful for a particular audience. They make sense of the world by identifying the significance of people, places, objects, and events in time. In international relations, international actors create strategic narratives to “construct a shared meaning of the past, present, and future of international politics to shape the behavior of domestic and international actors”</p> <p>DIPROMATS 2024 Task 2 is a multiclass multilabel classification problem. Given a series of predefined narratives of each international actor, systems must determine which narrative the tweets belong to. Systems will receive the description of each narrative and a few examples of tweets in both languages (English and Spanish) that belong to each of them (few-shot learning). A tweet may be associated with one, several or none of the narratives.</p> <p>The few-shot training data can be found here: <a href="https://doi.org/10.5281/zenodo.10820961" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10820961</a></p> <p>These are the testing datasets for Englsih and Spanish. They are provided without the keys so the large language models can't be contaminated. If you are interested on testing your system, write anselmo@lsi.uned.es for details on submission and leaderboards.</p>
Data and codes: Changing the Academic Gender Narrative through Open Access
<p>This Zenodo entry includes data and R codes used to generate the figures included in the manuscript "Changing the Academic Gender Narrative through Open Access", authored by members of the Curtin Open Knowledge Initiative (COKI). These include data that are either publicly available or derived through the COKI data infrastructure.</p> <p>The R file includes codes used to generate Figures 1, 2, 3, 4, 1A, 2A and 3A. It uses data contained in the files "au_data_all.csv", "au_groupings.csv", "uk_data_all.csv" and "uk_groupings.csv".</p> <p>This entry also includes the full data files (.csv and .xlsx) for Figures 5 and 6 included in the manuscript:</p> <ul> <li>Figure 5: ‘Percentages of women academic staff (headcount) compared to the total number of academics in the institution for 43 Australian universities by grouping, 2020’. The analysis is of publicly available data sourced from the Australian Department of Education, Skills and Employment.</li> <li>Figure 6: ‘Percentages of women academic staff (headcount) compared to the total number of academics in the institution for a subset of 165 United Kingdom higher education institutions by grouping, 2020’. The analysis is of publicly available data sourced from the United Kingdom Higher Education Statistics Agency (HESA).</li> </ul>
Experimental data for "Virtual Reality as a Tool for Promoting Reading via Enhanced Narrative Absorption and Empathy"
<p>This dataset contains data of the publication "Virtual Reality as a Tool for Promoting Reading via Enhanced Narrative Absorption and Empathy". It includes measure for the Story World Absorption Scale and the State Empathy Scale used to compare subjective experiences while reading on paper and reading in a virtual reality environment.</p> <p>Original paper: Pianzola, F., Bálint, K., and Weller, J. (2019). Virtual Reality as a Tool for Promoting Reading via Enhanced Narrative Absorption and Empathy. <em>Scientific Study of Literature 9</em>(2). https://doi.org/10.1075/ssol.19013.pia</p>
Questionnaire for evaluating data narratives
<p>File containing the evaluation questionnaire for the data narratives. The questionnaire describes 6 different scenarios, where the respondents have to choose which narrative is more appropriate, or define the one they would choose.</p>
Evaluation results for Data Narratives
<p>Excel file containing the results of the 12 responses to the questionnaire http://doi.org/10.5281/zenodo.234648</p> <p>The file also contains the graphs included on the paper http://dx.doi.org/10.1145/3025171.3025193</p>
Graphing/Markup Data: TNA SC8 Petitionary Texts and Community Narrative
<p>Cleaned CSV files of data samples taken from the British National Archives database; TNA petition XML/TEI data model for the purpose of digitizing and cataloguing documents from the TNA repository.</p> <p><em>The final iteration of this project will be an interactive web-based visual representation of medieval communication networks using petitionary texts. I am currently researching methods to reposition these 13th century petitions as a form of communication while viewing them as an early form of social media. Typically these petitions were either grievances or requests made to the king seeking favor or assistance. By analyzing the data that is found in each of these petitions both through a database found at the National Archives in the United Kingdom, I can look at the smaller storylines within the larger system. I am also studying the objects themselves including the handwritten information which is how I plan on transcribing and editing the texts using TEI markup. The goal is to make this model transferable for use with other collections of historical texts and for digital humanities projects where the collections, including the digitized images, the data, and the relationships established can be curated for educational use.</em></p>
Network formation as Narrative: Case Study Data
<p>This data is the companion to a forthcoming paper entitled Network Formation As Narrative In Computer Role-playing Games. It consists of several excel sheets and gephi files with some graphs of social network data from a campaign of Mount & Blade: Warband, a campaign of The Exile Princes, and some hand-curated data on networks presented in the narrative of the early part of Baldur's Gate 3.</p>
Data from: Neural correlates of multisensory enhancement in audiovisual narrative speech perception: a fMRI investigation
<p>This fMRI study investigated the effect of seeing articulatory movements of a speaker while listening to a naturalistic narrative stimulus. It had the goal to identify regions of the language network showing multisensory enhancement under synchronous audiovisual conditions. We expected this enhancement to emerge in regions known to underlie the integration of auditory and visual information such as the posterior superior temporal gyrus as well as parts of the broader language network, including the semantic system. To this end we presented 53 participants with a continuous narration of a story in auditory alone, visual alone, and both synchronous and asynchronous audiovisual speech conditions while recording brain activity using BOLD fMRI. We found multisensory enhancement in an extensive network of regions underlying multisensory integration and parts of the semantic network as well as extralinguistic regions not usually associated with multisensory integration, namely the primary visual cortex and the bilateral amygdala. Analysis also revealed involvement of thalamic brain regions along the visual and auditory pathways more commonly associated with early sensory processing. We conclude that under natural listening conditions, multisensory enhancement not only involves sites of multisensory integration but many regions of the wider semantic network and includes regions associated with extralinguistic sensory, perceptual and cognitive processing.</p>
Data from: Neural correlates of multisensory enhancement in audiovisual narrative speech perception: a fMRI investigation
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Data from: Characters matter: wow narratives shape affective responses to risk communication
Introduction <p class="MsoBodyText">Whereas scientists depend on the language of probability to relay information about hazards, risk communication may be more effective when embedding scientific information in narratives. The persuasive power of narratives is theorized to reside, in part, in narrative transportation. </p> Purpose <p>This study seeks to advance the science of stories in risk communication by measuring real-time affective responses as a proxy indicator for narrative transportation during science messages that present scientific information in the context of narrative.</p> Methods <p class="MsoBodyText">This study employed a within-subjects design in which participants (n=90) were exposed to eight science messages regarding flood risk. Conventional science messages using probability and certainty language represented two conditions. The remaining six conditions were narrative science messages that embedded the two conventional science messages within three story forms that manipulated the narrative mechanism of character selection. Informed by the Narrative Policy Framework, the characters portrayed in the narrative science messages were hero, victim, and victim-to-hero. Natural language processing techniques were applied to identify and rank hero and victim vocabularies from 45 resident interviews conducted in the study area; the resulting classified vocabulary was used to build each of the three story types. Affective response data were collected over 12 group sessions across three flood-prone communities in Montana. Dial response technology was used to capture continuous, second-by-second recording of participants' affective responses while listening to each of the eight science messages. Message order was randomized across sessions. ANOVA and three linear mixed-effects models were estimated to test our predictions.</p> Results <p>First, both probabilistic and certainty science language evoked negative affective responses with no statistical differences between them. Second, narrative science messages were associated with greater variance in affective responses than conventional science messages. Third, when characters are in action, variation in the narrative mechanism of character selection leads to significantly different affective responses. Hero and victim-to-hero characters elicit positive affective responses, while victim characters produce a slightly negative response.</p> Conclusions <p>In risk communication, characters matter in audience experience of narrative transportation as measured by affective responses.</p>
Data from: Effectiveness and meaningful use of paediatric surgical safety checklists and their implementation strategies: a systematic review with narrative synthesis
ObjectiveTo examine the effectiveness and meaningful use of pediatric surgical safety checklists (SSCs) and their implementation strategies through a systematic review with narrative synthesis. Summary Background Data Since the launch of the World Health Organization SSC, checklists have been integrated into surgical systems worldwide. Information is sparse on how SSCs have been integrated into the pediatric surgical environment. Methods A broad search strategy was created using Pubmed, Embase, CINAHL, Cochrane Central, Web of Science, Science Citation Index and Conference Proceedings Citation Index. Abstracts and full texts were screened independently, in duplicate for inclusion. Extracted study characteristic and outcomes generated themes explored through subgroup analyses and idea webbing. Results 1826 of 1921 studies were excluded after title and abstract review (kappa 0.77) and 47 after full-text review (kappa 0.86). 20 studies were of sufficient quality for narrative synthesis. Clinical outcomes were not affected by SSC introduction in studies without implementation strategies. A comprehensive SSC implementation strategy in developing countries demonstrated improved outcomes in high-risk surgeries. Narrative synthesis suggests that meaningful compliance is inconsistently measured and rarely achieved. Strategies involving feedback improved compliance. Stakeholder-developed implementation strategies, including team-based education achieved greater acceptance. Three studies suggest that parental involvement in the SSC is valued by parents, nurses and physicians, and may improve patient safety. Conclusions A SSC implementation strategy focused on pediatric patients and their families can achieve high acceptability and good compliance. SSCs' role in improving measures of pediatric surgical outcome is not well established but they may be effective when used within a comprehensive implementation strategy especially for high-risk patients in low-resource settings.
Reduced Gun Violence Frame Corpus data set for the Text2Story 2024 article: "Evaluating the Ability of Computationally Extracted Narrative Maps to Encode Media Framing"
<p><strong>Title: </strong>Simplified Gun Violence Frame Corpus (GVFC) Subset</p> <p><strong>Description:</strong><br>This data set is a simplified subset of the Gun Violence Frame Corpus (GVFC) from Liu et al. (2019). The original GVFC consists of 1300 news articles in English from multiple U.S. based sources extracted during the year 2018, focusing on media frames commonly used when reporting the issue of Gun Violence. The original data set has 9 types of frames, including both issue-specific and generic frames. Due to high computational costs in our analysis methods, we decreased the data set size from 1300 articles to 131 articles using stratified sampling, maintaining the original distribution of the frame labels. We also manually searched for the original sources of each article based on its headline and added the missing temporal information and news source to the data set, as it was required by our algorithms.</p> <p>To further reduce the complexity of the framing model and account for the smaller data set size, we grouped the original nine frames into three higher-level frames:</p> <p>1. Frame 1: Political Issues - Combining the first, second, and third frames, which focus on political issues mostly related to gun control.<br>2. Frame 2: Public Services - Combining the fourth and fifth frames, which focus on mental healthcare issues, as well as school and public safety.<br>3. Frame 3: Cultural and Societal Issues - Combining the last four frames, which are oriented towards cultural or societal issues, including discussions around race and ethnicity, public opinion, and economic consequences.</p> <p>The resulting simplified data set contains 131 news articles, each labeled with one of the three higher-level frames, along with the necessary temporal information and news source for the narrative extraction process.</p> <p>If you use this data set, please make sure to cite the original GVFC paper and our workshop paper please. </p> <p><strong>References:</strong></p> <ol> <li>Liu et al. (2019) "Detecting Frames in News Headlines and Its Application to Analyzing News Framing Trends Surrounding US Gun Violence", 23rd Conference on Computational Natural Language Learning (CoNLL 2019).</li> <li>Concha Macías, Sebastián and Keith Norambuena, Brian (2024). "Evaluating the Ability of Computationally Extracted Narrative Maps to Encode Media Framing", Text2Story 2024 Workshop, ECIR 2024.</li> </ol>
DIPROMATS 2024 - Shared Task 2: few-shot training data for narrative identification
<p>Narratives are causally connected sequences of events that are selected and evaluated as meaningful for a particular audience. They make sense of the world by identifying the significance of people, places, objects, and events in time. In international relations, international actors create strategic narratives to “construct a shared meaning of the past, present, and future of international politics to shape the behavior of domestic and international actors”</p> <p>DIPROMATS 2024 Task 2 is a multiclass multilabel classification problem. Given a series of predefined narratives of each international actor, systems must determine which narrative the tweets belong to. Systems will receive the description of each narrative and a few examples of tweets in both languages (English and Spanish) that belong to each of them (few-shot learning). A tweet may be associated with one, several or none of the narratives.</p> <p>These are the few-shot training datasets for Englsih and Spanish.</p> <p>These files don't contain the narratives description. You can find them in the testing dataset:</p> <p>Peñas, A., Fraile-Hernández, J. M., Moral, P., Rodrigo, Á., Deriu, J., Sharma, R., Centeno, R., Rodríguez-García, R., Giedemann, P., & Reyes-Montesinos, J. (2024). DIPROMATS 2024 - Shared Task 2: testing data for narrative identification (1.0.0) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.12663310" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12663310</a></p>
Data from: Electrophysiological correlates of semantic dissimilarity reflect the comprehension of natural, narrative speech
People routinely hear and understand speech at rates of 120–200 words per minute [1, 2]. Thus, speech comprehension must involve rapid, online neural mechanisms that process words' meanings in an approximately time-locked fashion. However, in the context of continuous speech, electrophysiological evidence for such time-locked processing has been lacking. Whilst valuable insights into the semantic processing of speech have been provided by the "N400 component" of the event-related potential [3-6], this literature has been dominated by paradigms using incongruous words within specially constructed sentences, and may not accurately reflect natural, narrative speech comprehension. Building on the discovery that cortical activity "tracks" the dynamics of running speech [7-9], and psycholinguistic work both demonstrating [10-12] and modeling [13-15] how context rapidly impacts on word processing, we describe a new approach for deriving an electrophysiological correlate of natural speech comprehension. We used a computational model [16] to quantify the meaning carried by each word based on how semantically dissimilar it was to its preceding context and then regressed this quantity against electroencephalographic (EEG) data recorded from subjects as they listened to narrative speech. This produced a prominent negativity at a time-lag of 200–600 ms on centro-parietal EEG channels, characteristics common to the N400. Applying this approach to EEG datasets involving time-reversed speech, cocktail party attention and audiovisual speech-in-noise demonstrated that this response was very sensitive to whether or not subjects understood the speech they heard. These findings demonstrate that, when successfully comprehending natural speech, the human brain responds to the contextual semantic content of each word in a relatively time-locked fashion.
Data from the article: Narrative Risk Communication as a Lingua Franca for Environmental Hazard Preparation
<p>Incorporating narrative elements into risk communication may encourage preparation for environmental hazards in ways that scientific language alone does not. We integrate narrative theory, narrative persuasion, and risk theories into a Narrative Risk Communication Framework and then assess the effectiveness of character selection as a narrative mechanism in scientific risk communication as compared to conventional science messaging alone. We utilize a survey experiment with residents along the flood-prone Yellowstone River in Montana and analyze the resulting data with a parallel and serial mediation statistical model. We find that positive affective response mediates the influence of narratives featuring hero character language. Positive affective response appears to overcome the risk perception paradox both by circumventing rational analysis of risk and by shaping risk perception. Overall, the results suggest that inspirational hero language is superior to language of fear or victimization in encouraging preparation – an important lesson for practitioners working to help citizens prepare for environmental disasters.</p>
Experimental Data for "Is a Picture Worth a Thousand Words? Effects of Foregrounded Multimodal and Narrative Features"
<p>This dataset contains data of the publication "Is a Picture Worth a Thousand Words? Effects of Foregrounded Multimodal and Narrative Features". It includes measures for the Story World Absorption Scale, the Transformative Reading Scale, and the Empathy subscale of the Literary Response Questionnaire used to test the effect of multimodal features of multimodal novels and narrative perspectives and their interactive effects on reading-induced imagery and emotional reactions in the process of reading. </p>
Data from: Electrophysiological correlates of semantic dissimilarity reflect the comprehension of natural, narrative speech
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Data from the article: Narrative Risk Communication as a Lingua Franca for Environmental Hazard Preparation
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Data from: Characters matter: how narratives shape affective responses to risk communication
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Data from: Building the graph of medicine from millions of clinical narratives
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