Pub Date : 2023-11-13DOI: 10.1177/01655515231205482
Won-Ki Moon, Soobum Lee
Although numerous studies have explained the flow of misinformation, finding studies that theoretically examine the psychological factors related to individuals’ information behaviours is difficult. Social media data or meta-level analyses have limitations in providing an understanding of behaviours and processes at the individual level. Accordingly, this study aims to construct a predictive model for biased information seeking and sharing as a response to misinformation, which is information without the certainty of its truth, through a survey ( N = 602). Applying social psychological concepts (i.e. social identity theory), two types of social identities were proposed as key factors of biased information seeking and sharing in the research model. Our model allows forecasting of what types of individuals are more likely to skip the fact-checking process and share misinformation.
{"title":"Who seeks and shares misinformation about politicians? Focusing on the roles of party- and politician-level social identities","authors":"Won-Ki Moon, Soobum Lee","doi":"10.1177/01655515231205482","DOIUrl":"https://doi.org/10.1177/01655515231205482","url":null,"abstract":"Although numerous studies have explained the flow of misinformation, finding studies that theoretically examine the psychological factors related to individuals’ information behaviours is difficult. Social media data or meta-level analyses have limitations in providing an understanding of behaviours and processes at the individual level. Accordingly, this study aims to construct a predictive model for biased information seeking and sharing as a response to misinformation, which is information without the certainty of its truth, through a survey ( N = 602). Applying social psychological concepts (i.e. social identity theory), two types of social identities were proposed as key factors of biased information seeking and sharing in the research model. Our model allows forecasting of what types of individuals are more likely to skip the fact-checking process and share misinformation.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"130 50","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136352224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-31DOI: 10.1177/01655515231205496
Hanna Shmagun, Jangsup Shim, Jaesoo Kim, Kwang-Nam Choi, Charles Oppenheim
The coronavirus pandemic has illustrated the lack of a holistic approach in implementing Open Science (OS), leading to an inability to fully utilise its potential to inform prompt, evidence-based policy responses. In this view, this study aims to identify and categorise the factors influencing the adoption of OS and proposes possible actions for decision-makers to develop relevant policies. To achieve this, semi-structured interviews were conducted with 36 experts from Australia, France, the Netherlands, South Korea, the United Kingdom, and the United States as well as eminent international entities. During the interviews, they were asked to answer a range of questions that emerged from a systematic literature review. The responses were coded and analysed using a grounded theory approach. This led to the identification of four thematic clusters, containing a total of 24 factors that can either enable or inhibit OS practices, namely, (a) external; (b) institutional and regulatory; (c) resource-related; and (d) individual and motivational. Drawing upon Ostrom’s Institutional Analysis and Development framework, we also propose a conceptual model that integrates these factors, accompanied with corresponding actions, into a tangible process of OS policy design and implementation.
{"title":"Identifying key factors and actions: Initial steps in the Open Science Policy Design and Implementation Process","authors":"Hanna Shmagun, Jangsup Shim, Jaesoo Kim, Kwang-Nam Choi, Charles Oppenheim","doi":"10.1177/01655515231205496","DOIUrl":"https://doi.org/10.1177/01655515231205496","url":null,"abstract":"The coronavirus pandemic has illustrated the lack of a holistic approach in implementing Open Science (OS), leading to an inability to fully utilise its potential to inform prompt, evidence-based policy responses. In this view, this study aims to identify and categorise the factors influencing the adoption of OS and proposes possible actions for decision-makers to develop relevant policies. To achieve this, semi-structured interviews were conducted with 36 experts from Australia, France, the Netherlands, South Korea, the United Kingdom, and the United States as well as eminent international entities. During the interviews, they were asked to answer a range of questions that emerged from a systematic literature review. The responses were coded and analysed using a grounded theory approach. This led to the identification of four thematic clusters, containing a total of 24 factors that can either enable or inhibit OS practices, namely, (a) external; (b) institutional and regulatory; (c) resource-related; and (d) individual and motivational. Drawing upon Ostrom’s Institutional Analysis and Development framework, we also propose a conceptual model that integrates these factors, accompanied with corresponding actions, into a tangible process of OS policy design and implementation.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135870411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-31DOI: 10.1177/01655515231204802
Jing Dong, Yangyang Kang, Jiawei Liu, Changlong Sun, Shu Fan, Huchong Jin, Dan Wu, Zhuoren Jiang, Xi Niu, Xiaozhong Liu
Active learning in machine learning is an effective approach to reducing the cost of human efforts for generating labels. The iterative process of active learning involves a human annotation step, during which crowdsourcing could be leveraged. It is essential for organisations adopting the active learning method to obtain a high model performance. This study aims to identify effective crowdsourcing interaction designs to promote the quality of human annotations and therefore the natural language processing (NLP)-based machine learning model performance. Specifically, the study experimented with four human-centred design techniques: highlight, guidelines, validation and text amount. Based on different combinations of the four design elements, the study developed 15 different annotation interfaces and recruited crowd workers to annotate texts with these interfaces. Annotated data under different designs were used separately to iteratively train a machine learning model. The results show that the design techniques of highlight and guideline play an essential role in improving the quality of human labels and therefore the performance of active learning models, while the impact of validation and text amount on model performance can be either positive in some cases or negative in other cases. The ‘simple’ designs (i.e. D1, D2, D7 and D14) with a few design techniques contribute to the top performance of models. The results provide practical implications to inspire the design of a crowdsourcing labelling system used for active learning.
{"title":"Human-centred design on crowdsourcing annotation towards improving active learning model performance","authors":"Jing Dong, Yangyang Kang, Jiawei Liu, Changlong Sun, Shu Fan, Huchong Jin, Dan Wu, Zhuoren Jiang, Xi Niu, Xiaozhong Liu","doi":"10.1177/01655515231204802","DOIUrl":"https://doi.org/10.1177/01655515231204802","url":null,"abstract":"Active learning in machine learning is an effective approach to reducing the cost of human efforts for generating labels. The iterative process of active learning involves a human annotation step, during which crowdsourcing could be leveraged. It is essential for organisations adopting the active learning method to obtain a high model performance. This study aims to identify effective crowdsourcing interaction designs to promote the quality of human annotations and therefore the natural language processing (NLP)-based machine learning model performance. Specifically, the study experimented with four human-centred design techniques: highlight, guidelines, validation and text amount. Based on different combinations of the four design elements, the study developed 15 different annotation interfaces and recruited crowd workers to annotate texts with these interfaces. Annotated data under different designs were used separately to iteratively train a machine learning model. The results show that the design techniques of highlight and guideline play an essential role in improving the quality of human labels and therefore the performance of active learning models, while the impact of validation and text amount on model performance can be either positive in some cases or negative in other cases. The ‘simple’ designs (i.e. D1, D2, D7 and D14) with a few design techniques contribute to the top performance of models. The results provide practical implications to inspire the design of a crowdsourcing labelling system used for active learning.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135872351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-31DOI: 10.1177/01655515231202757
Carlos Brys, Ismael Navas-Delgado, José F Aldana-Montes
This article presents a novel approach to wildfire risk assessment and behaviour prediction by leveraging open geospatial data and ontologies. The proposed methodology includes a spatially weighted index model and multicriteria analysis to represent the risk of forest fires in the affected area. It bridges gaps in theory and practice, offering a comprehensive solution for evaluating potential forest fire risk in near real time, predicting fire behaviour and elucidating the semantics of fire management. During dry and hot conditions, forest fires tend to escalate. Hence, we propose an algorithm that combines experts’ empirical criteria and open-source data to identify dangerous fires in near real time, aiding authorities in directing attention to the riskiest areas. The objective is to predict forest fire behaviour, a complex and nonlinear system influenced by dynamic factors such as weather conditions, topography and land use. Our methodology enables real-time assessment of potential forest fire risks, complemented by predictive fire behaviour scenarios and a descriptive ontology of fire management semantics. We examine existing fire-related ontologies and propose a comprehensive one encompassing incident descriptions, firefighting resources, actor interrelations and knowledge for effective action. By classifying fire sources, our algorithm enables strategic decision-making to prevent uncontrolled fires. This solution significantly enhances data using semantic and spatial relationships among wildfire resources. Furthermore, we demonstrate how ontologies improve data integration and interoperability among diverse systems and organisations involved in forest fire risk management, fostering better coordination and faster responses to critical situations. To facilitate decision-making, we create decision-making scenarios linked to analysed hot spots, drawing from open hot spot data such as National Aeronautics and Space Administration (NASA) Fire Information for Resource Management System (FIRMS), OpenStreetMap (OSM), OpenWeatherMap (OWM) and OpenTopoData (OTD). We propose an ordinal and linguistic classification system (F1–F5) denoting risk levels as low, moderate, high, very high and extreme. These values are obtained through factor aggregation and fuzzy logic. A publicly accessible, interactive web map displays the results derived from this model. Overall, our contributions to wildfire risk management provide authorities with a valuable tool to make informed decisions and mitigate the damaging effects of wildfires.
{"title":"Wildfire risk weighting and behaviour prediction using open geospatial data and ontologies","authors":"Carlos Brys, Ismael Navas-Delgado, José F Aldana-Montes","doi":"10.1177/01655515231202757","DOIUrl":"https://doi.org/10.1177/01655515231202757","url":null,"abstract":"This article presents a novel approach to wildfire risk assessment and behaviour prediction by leveraging open geospatial data and ontologies. The proposed methodology includes a spatially weighted index model and multicriteria analysis to represent the risk of forest fires in the affected area. It bridges gaps in theory and practice, offering a comprehensive solution for evaluating potential forest fire risk in near real time, predicting fire behaviour and elucidating the semantics of fire management. During dry and hot conditions, forest fires tend to escalate. Hence, we propose an algorithm that combines experts’ empirical criteria and open-source data to identify dangerous fires in near real time, aiding authorities in directing attention to the riskiest areas. The objective is to predict forest fire behaviour, a complex and nonlinear system influenced by dynamic factors such as weather conditions, topography and land use. Our methodology enables real-time assessment of potential forest fire risks, complemented by predictive fire behaviour scenarios and a descriptive ontology of fire management semantics. We examine existing fire-related ontologies and propose a comprehensive one encompassing incident descriptions, firefighting resources, actor interrelations and knowledge for effective action. By classifying fire sources, our algorithm enables strategic decision-making to prevent uncontrolled fires. This solution significantly enhances data using semantic and spatial relationships among wildfire resources. Furthermore, we demonstrate how ontologies improve data integration and interoperability among diverse systems and organisations involved in forest fire risk management, fostering better coordination and faster responses to critical situations. To facilitate decision-making, we create decision-making scenarios linked to analysed hot spots, drawing from open hot spot data such as National Aeronautics and Space Administration (NASA) Fire Information for Resource Management System (FIRMS), OpenStreetMap (OSM), OpenWeatherMap (OWM) and OpenTopoData (OTD). We propose an ordinal and linguistic classification system (F1–F5) denoting risk levels as low, moderate, high, very high and extreme. These values are obtained through factor aggregation and fuzzy logic. A publicly accessible, interactive web map displays the results derived from this model. Overall, our contributions to wildfire risk management provide authorities with a valuable tool to make informed decisions and mitigate the damaging effects of wildfires.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"24 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135870922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-31DOI: 10.1177/01655515231205499
Faten Jaber, Muneer Abbad
This article examines the negative consequences that can arise from the utilisation of innovative data practices implemented by organisations. While these technologies offer significant value, their improper implementation can lead to harmful practices that undermine the rights of individuals within societies. Through a systematic literature review of 383 articles employing the realistic evaluation theory, this study synthesises key findings to identify the contextual factors that contribute to these harmful practices. The results highlight the challenges posed by the characteristics of Big Data, often resulting in haphazard data implementation scenarios. Three critical mechanisms, namely data transparency, biases, and breaches, interact with these implementation contexts, leading to adverse outcomes that compromise individual empowerment, societal fairness, and personal privacy. In addition, this article identifies important areas for future research and provides recommendations for policymakers to effectively manage the negative aspects of data practices, ensuring sustainability within the digital ecosystem.
{"title":"A realistic evaluation of the dark side of data in the digital ecosystem","authors":"Faten Jaber, Muneer Abbad","doi":"10.1177/01655515231205499","DOIUrl":"https://doi.org/10.1177/01655515231205499","url":null,"abstract":"This article examines the negative consequences that can arise from the utilisation of innovative data practices implemented by organisations. While these technologies offer significant value, their improper implementation can lead to harmful practices that undermine the rights of individuals within societies. Through a systematic literature review of 383 articles employing the realistic evaluation theory, this study synthesises key findings to identify the contextual factors that contribute to these harmful practices. The results highlight the challenges posed by the characteristics of Big Data, often resulting in haphazard data implementation scenarios. Three critical mechanisms, namely data transparency, biases, and breaches, interact with these implementation contexts, leading to adverse outcomes that compromise individual empowerment, societal fairness, and personal privacy. In addition, this article identifies important areas for future research and provides recommendations for policymakers to effectively manage the negative aspects of data practices, ensuring sustainability within the digital ecosystem.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135872220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study modelled the online environment characteristics and message characteristics that predict news sharing among social media users. This study’s data were obtained from a cross-sectional national survey conducted in Nigeria. Qualtrics was used to recruit data from 1320 participants in Nigeria. The participants were recruited via a stratified quota sampling which reflected the country’s census statistics for gender and age. We found the message characteristics to predict news-sharing behaviour among social media users in Nigeria. By implication, the characteristics of a message encountered online influence the news-sharing behaviour of social media users. We also found that the online environment characteristics predict news-sharing behaviour, which implies that the external factor, that is, the relationship a user has with his network members, predicts sharing behaviour. Some theoretical and practical implications were provided to conclude the study.
{"title":"Modelling the factors that determine online news-sharing behaviour of social media users: The role of perceived message and online environmental characteristics","authors":"Risu Na, Yaqin Wang, Buqi Na, Yucheng Ning, Oberiri Destiny Apuke","doi":"10.1177/01655515231205477","DOIUrl":"https://doi.org/10.1177/01655515231205477","url":null,"abstract":"This study modelled the online environment characteristics and message characteristics that predict news sharing among social media users. This study’s data were obtained from a cross-sectional national survey conducted in Nigeria. Qualtrics was used to recruit data from 1320 participants in Nigeria. The participants were recruited via a stratified quota sampling which reflected the country’s census statistics for gender and age. We found the message characteristics to predict news-sharing behaviour among social media users in Nigeria. By implication, the characteristics of a message encountered online influence the news-sharing behaviour of social media users. We also found that the online environment characteristics predict news-sharing behaviour, which implies that the external factor, that is, the relationship a user has with his network members, predicts sharing behaviour. Some theoretical and practical implications were provided to conclude the study.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135872640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-27DOI: 10.1177/01655515231202758
Arslan Sheikh, Joanna Richardson
Open access is a scholarly publishing model that has emerged as an alternative to traditional subscription-based journal publishing. This study explores the adoption of the open access movement worldwide and the role that libraries can play in addressing those factors which are slowing its progress within developing countries. The study has drawn upon both qualitative data from a focused literature review and quantitative data from major open access platforms. The results indicate that while the open access movement is steadily gaining acceptance worldwide, the progress in developing countries within geographical areas such as Africa, Asia and Oceania is quite a bit slower. Two significant factors are the cost of publishing fees and the lack of institutional open access mandates and policies to encourage uptake. The study provides suggested strategies for academic libraries to help overcome current challenges.
{"title":"Open access movement in the scholarly world: Pathways for libraries in developing countries","authors":"Arslan Sheikh, Joanna Richardson","doi":"10.1177/01655515231202758","DOIUrl":"https://doi.org/10.1177/01655515231202758","url":null,"abstract":"Open access is a scholarly publishing model that has emerged as an alternative to traditional subscription-based journal publishing. This study explores the adoption of the open access movement worldwide and the role that libraries can play in addressing those factors which are slowing its progress within developing countries. The study has drawn upon both qualitative data from a focused literature review and quantitative data from major open access platforms. The results indicate that while the open access movement is steadily gaining acceptance worldwide, the progress in developing countries within geographical areas such as Africa, Asia and Oceania is quite a bit slower. Two significant factors are the cost of publishing fees and the lack of institutional open access mandates and policies to encourage uptake. The study provides suggested strategies for academic libraries to help overcome current challenges.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"46 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136262296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-27DOI: 10.1177/01655515231204800
Xiaobo Tang, Wenxuan Shi, Renli Wu, Shixuan Li
The increasing prevalence of large research teams in contemporary science has prompted an investigation into the trends of team size in library and information science (LIS). In this study, we analysed 103,299 LIS publications written by 129,560 unique authors between 2000 and 2020 sourced from the Microsoft Academic Graph (MAG) data sets. We conducted a temporal analysis from multiple dimensions, including journal quartiles, research topics and researchers with varying impact levels. In addition, we employed two multivariate linear regression models – with and without author fixed effects – to scrutinise the relationship between team size and publication impact. Our findings reveal continuous growth in LIS team size. Notably, publications in higher-quartile journals tend to have larger teams; the team size of technical topic publications is generally larger than that of theoretical topic publications; and researchers with a higher h-index are able to assemble larger teams. Although we observed that co-authored papers have a higher average citation impact than single-authored papers, the overall positive impact of team expansion on citation growth is not always significant within the common LIS team size range (three to six authors). Our research suggests that indiscriminately increasing the size of a team may not be a prudent decision.
{"title":"The expansion of team size in library and information science (LIS): <i>Is bigger always better?</i>","authors":"Xiaobo Tang, Wenxuan Shi, Renli Wu, Shixuan Li","doi":"10.1177/01655515231204800","DOIUrl":"https://doi.org/10.1177/01655515231204800","url":null,"abstract":"The increasing prevalence of large research teams in contemporary science has prompted an investigation into the trends of team size in library and information science (LIS). In this study, we analysed 103,299 LIS publications written by 129,560 unique authors between 2000 and 2020 sourced from the Microsoft Academic Graph (MAG) data sets. We conducted a temporal analysis from multiple dimensions, including journal quartiles, research topics and researchers with varying impact levels. In addition, we employed two multivariate linear regression models – with and without author fixed effects – to scrutinise the relationship between team size and publication impact. Our findings reveal continuous growth in LIS team size. Notably, publications in higher-quartile journals tend to have larger teams; the team size of technical topic publications is generally larger than that of theoretical topic publications; and researchers with a higher h-index are able to assemble larger teams. Although we observed that co-authored papers have a higher average citation impact than single-authored papers, the overall positive impact of team expansion on citation growth is not always significant within the common LIS team size range (three to six authors). Our research suggests that indiscriminately increasing the size of a team may not be a prudent decision.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"73 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136317203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-24DOI: 10.1177/01655515231202762
Shiji Chen, Xuyan Ren
The impact of interdisciplinarity is a popular research topic, but most studies on this subject focus mainly on scientific impact. In recent years, social media platforms have become useful tools for assessing broader effects beyond scientific or academic impacts. Thus, exploring the effect of interdisciplinarity on social media platforms may yield interesting results. In order to examine the relationship between interdisciplinarity and social media attention, we analysed all publications in the Scopus database for the years 2018 and 2019. Three social media platforms with the highest coverage of research articles, Mendeley, Twitter and Facebook, and three common interdisciplinarity indicators, Leinster-Cobbold diversity indices (LCDiv), Rao-Stirling diversity (RS) and DIV, were applied to cross-validate our findings. It appears that interdisciplinarity does increase social media attention on Mendeley, Twitter and Facebook alike. The results indicate that interdisciplinary research indeed can attract more social media attention.
{"title":"Does interdisciplinarity attract more social media attention?","authors":"Shiji Chen, Xuyan Ren","doi":"10.1177/01655515231202762","DOIUrl":"https://doi.org/10.1177/01655515231202762","url":null,"abstract":"The impact of interdisciplinarity is a popular research topic, but most studies on this subject focus mainly on scientific impact. In recent years, social media platforms have become useful tools for assessing broader effects beyond scientific or academic impacts. Thus, exploring the effect of interdisciplinarity on social media platforms may yield interesting results. In order to examine the relationship between interdisciplinarity and social media attention, we analysed all publications in the Scopus database for the years 2018 and 2019. Three social media platforms with the highest coverage of research articles, Mendeley, Twitter and Facebook, and three common interdisciplinarity indicators, Leinster-Cobbold diversity indices (LCDiv), Rao-Stirling diversity (RS) and DIV, were applied to cross-validate our findings. It appears that interdisciplinarity does increase social media attention on Mendeley, Twitter and Facebook alike. The results indicate that interdisciplinary research indeed can attract more social media attention.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"20 11-12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135266846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-24DOI: 10.1177/01655515231202761
Shouqiang Sun, Ziming Zeng, Qingqing Li
Murals unearthed in China have outstanding regional characteristics and one of the largest period spans in scale and variety. To explore the visual distinguishability and topic autocorrelation of murals unearthed in China from the spatial perspective, multiple classification models are employed to classify murals unearthed in China through visual features. Then, the k-means is employed to mine topics, and they are analysed through topic intensities (TIs), Moran’s Index (MI) and spatial topic concentration degrees (STCDs). In addition, the characteristics of topic distribution and evolution are summarised and revealed in the spatial dimension. From a spatial perspective, it verifies the distinguishability of visual features of murals through ViT_BOW_GNB, and the precision of this model is 98.17%. Thirteen topics are clustered through k-means, and the distribution of mural topics is spatial autocorrelation according to MI. Besides, the topic evolves from the political centre to the surrounding area, and the topics with high intensities are highly concentrated in spatial. This study reveals the spatial characteristics of the mural at the level of visual features and semantics, which facilitates the digital management, conservation and knowledge discovery of cultural heritage resources.
{"title":"Exploring the visual distinguishability and topic autocorrelation of murals unearthed in China from the spatial perspective","authors":"Shouqiang Sun, Ziming Zeng, Qingqing Li","doi":"10.1177/01655515231202761","DOIUrl":"https://doi.org/10.1177/01655515231202761","url":null,"abstract":"Murals unearthed in China have outstanding regional characteristics and one of the largest period spans in scale and variety. To explore the visual distinguishability and topic autocorrelation of murals unearthed in China from the spatial perspective, multiple classification models are employed to classify murals unearthed in China through visual features. Then, the k-means is employed to mine topics, and they are analysed through topic intensities (TIs), Moran’s Index (MI) and spatial topic concentration degrees (STCDs). In addition, the characteristics of topic distribution and evolution are summarised and revealed in the spatial dimension. From a spatial perspective, it verifies the distinguishability of visual features of murals through ViT_BOW_GNB, and the precision of this model is 98.17%. Thirteen topics are clustered through k-means, and the distribution of mural topics is spatial autocorrelation according to MI. Besides, the topic evolves from the political centre to the surrounding area, and the topics with high intensities are highly concentrated in spatial. This study reveals the spatial characteristics of the mural at the level of visual features and semantics, which facilitates the digital management, conservation and knowledge discovery of cultural heritage resources.","PeriodicalId":54796,"journal":{"name":"Journal of Information Science","volume":"31 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135267897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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