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This ongoing study employs citation context analysis to examine the citation functions in social sciences and humanities (SS&H) disciplines. The analyses focus on the uses of organic/perfunctory citations and confirmative/ negational citations. In this poster, we will present the preliminary findings from the completed analysis on Chinese history research papers. Chinese history authors used a large amount of perfunctory citations. The percentage of negational citations was also high, and many papers have negated a previous research. It has seriously challenged the citation analysis assumptions that citations are of equal contribution and that citation means author endorsement of previous literatures. We will continue to complete the analyses for the other chosen SS&H disciplines, and we encourage other researchers to extend the analysis to other subject areas and in other countries or languages so as to better understand researchers' citation behavior and to better assess the applicability of citation analysis in different domains. [ABSTRACT FROM AUTHOR]

This paper reports on the development of a metadata application profile (AP), MetaFAIR, designed to support research data management (RDM) to make research data findable, accessible, interoperable, and reusable. The development of MetaFAIR followed a three‐step process that included learning about the characteristics of datasets from researchers to establish their context and requirements, as well as iterative design and testing with researchers' feedback. Guided by the FAIR principles (Findability, Accessibility, Interoperability, and Reusability), MetaFAIR focuses on accommodating description needs particular to computational social science datasets while seeking to provide general enough elements to describe data collections across many different domains. In this paper, MetaFAIR is placed in the context of historical and recent developments in the areas of RDM and application profile creation; following this contextualization, the paper describes the central considerations and challenges of the MetaFAIR development process and discusses its significance for future work in RDM. [ABSTRACT FROM AUTHOR]

Although open access (OA) to research outputs has been proven to improve research readership, citation, and impact, the uptake of OA in some disciplines has remained low. In this paper, we investigated and compared OA publishing practices of early career and mid‐career researchers in the Humanities, Arts, and Social Sciences (HASS) disciplines in Canada. The descriptive survey design with the use of online questionnaire was employed. Participants were drawn from a group of 15 public research universities via their openly available emails on university websites. Survey data was analyzed with descriptive and inferential statistics. Findings show that in the last three years, 74.1% of mid‐career researchers have published in OA journals, compared to 63.1% of early career researchers. However, OA publishing of monographs (21.3%) and conference proceedings (29.9%), as well as the frequency and extent OA publishing remains low among all participants. ANOVA results (F [2, 218] = 3.683, p =.027, 휂2 =.033) showed that 3.3% of the variance in researchers' OA publishing frequency can be attributed to their disciplines. Overall, OA publishing among researchers in the HASS disciplines is still low. Hence, there is a need to identify factors that facilitate or hinder HASS researchers' OA publishing. [ABSTRACT FROM AUTHOR]

It has always been argued that social sciences and humanities (SSH) impact evaluation calls for a broader range of indicators than only bibliometric indicators. This study analyzes the performance of scientific SSH publications using 1,327,924 records from the Social Sciences Citation Index (SSCI) and the Arts & Humanities Citation Index (A&HCI), and 629,586 records from Altmetric.com. The research covers a period of 5 years (2013–2017); three publication types (articles, reviews, and proceedings papers); four selected subject fields; three citation indicators; and 13 altmetric indicators. The comparative analysis of SSH performance is studied in both citation and altmetric pattern, and an attempt is made to interpret the results in both the metric and discipline contexts. Major contributions of this study include the extension of analysis methods for the SSH, as well as the validation of altmetric indicators. [ABSTRACT FROM AUTHOR]

In this paper, we analyse how three social science data archives (SSDA) have adapted to provide value to different stakeholders over time. Drawing on historical administrative documents and interviews with current and former staff at three long standing SSDA, we examine how these archives have provided value, to whom, and how they have situated themselves vis‐à‐vis alternative archives over 20‐40 year time spans. Although data archives have been in operation for decades, how they have sustained themselves over time by continuing to provide value to stakeholders in changing conditions is less well understood. Studies of value have tended to focus on a snapshot in time rather than providing a view that emphasizes change over time. We conclude with a comparative analysis of changes in value across archives and suggestions for future work [ABSTRACT FROM AUTHOR]

ABSTRACT This paper reports on the user centered, formative evaluation of tools and the validation of models for the analysis of historical textbooks in the context of the digital history project Children and their World. The goal of the project is to create methods for computer-supported, interactive analysis that can be applied to a large corpus of historical textbooks on history and geography (∼5000 volumes). A first version of a tool for text analysis has been created based on a user centered design process, including a contextual study on current work practices of historians, participative design workshops, and the prioritization of requirements with the project stakeholders. In addition, several generations of text models used in these tools have been iteratively evaluated by the historians in the project. In the context of a cooperative validation study, researchers have used these tools to examine existing hypotheses from the field. The method enables the validation of text models regarding established knowledge, provides additional insights into the requirements for tools and visualizations, and helps to strengthen the expert users' trust in the tools. Based on the findings, this paper proposes four principles for the analysis of a corpus of historical texts. Moreover, the methods presented are discussed regarding the application of user centered design in the context of digital humanities projects. [ABSTRACT FROM AUTHOR]

In this paper we describe the rationale behind a panel concerning the transdisciplinary approaches to critical data studies. We illuminate emerging modes of conducting critical data studies research and highlights the interdisciplinary opportunities within future research directions. We describe the format for the panel and the themes that will be covered by each of the author. By having this panel to occur it creates a space for interdisciplinary dialogues on a timely topic that touches various sub‐ fields of information science along with the broader social science disciplines in the academy. [ABSTRACT FROM AUTHOR]

Scholarly communication has the scope to transcend the limitations of the physical world through social media's extended coverage and shortened information paths. Accordingly, publishers have created profiles for their journals in Twitter to promote their publications and to initiate discussions with public. This paper investigates the Twitter presence of humanities and social sciences (HSS) journal titles obtained from mainstream citation indices, by analysing the interaction and communication patterns. This study utilizes webometric data collection, descriptive analysis, and social network analysis. Findings indicate that the presence of HSS journals in Twitter across disciplines is not yet substantial. Sharing of general websites appears to be the key activity performed by HSS journals in Twitter. Among them, web content from news portals and magazines are highly disseminated. Sharing of research articles and retweeting was not majorly observed. Inter‐journal communication is apparent within the same citation index, but it is very minimal with journals from the other index. However, there seems to be an effort to broaden communication beyond the research community, reaching out to connect with the public. [ABSTRACT FROM AUTHOR]

This paper addresses the introduction of Semantic Web and Linked Data technology in Social Science and Humanities research. On the basis of a sample of existing research projects, we examine the impact that the technology has on the research methodology. Three main points of impact were observed. The first is the epistemological foundations of the research, including a focus on individual entities in the research area (or "atomization"), the reification of research objects, and the favouring of analytical skills from researchers. Secondly, in the data analysis phase, research relies more heavily on technical skills during data discovery and processing, and the technology induces growing confusion between data and metadata. Thirdly, we show how the types of models that are built often imply a new encoding of already existing information. [ABSTRACT FROM AUTHOR]

In this paper, we explore new approaches for combining manual and automatic content analysis. We compare three approaches to topic modelling: Latent Semantic Analysis (LSA), Latent Dirichlet Allocation (LDA), and Hierarchical Dirichlet Process (HDP). We applied all three approaches to study a corpus of 21,085 free‐response answers to questions from the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. We built topic models using the algorithms. Our preliminary results indicate that LSA and LDA yielded more useful results than HDP. We thematically analyzed the topic models and found similarities and differences in the factors that influenced patients' satisfaction with doctors and nurses. [ABSTRACT FROM AUTHOR]

Publishing research data is widely expected to increase its reuse and to inspire new research. In the social sciences, data from surveys, interviews, polls, and statistics are primary resources for research. There is a long tradition to collect and offer research data in data archives and online repositories. Researchers use these systems to identify data relevant to their research. However, especially in data search, users' complex information needs seem to collide with the capabilities of data search systems. The search capabilities, in turn, depend to a high degree upon the metadata schemes used to describe the data. In this research, we conducted an online survey with 72 social science researchers who expressed their individual information needs for research data like they would do when asking a colleague for help. We analyzed these information needs and attributed their different components to the categories: topic, metadata, and intention. We compared these categories and their content to existing metadata models of research data and the search and filter opportunities offered in existing data search systems. We found a mismatch between what users have as a requirement for their data and what is offered on metadata level and search system possibilities. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper investigates the landscape of data-sharing practices in social sciences via the data sharing profile approach. Guided by two pre-existing conceptual frameworks, Knowledge Infrastructure (KI) and the Theory of Remote Scientific Collaboration (TORSC), we design and test a profile tool that consists of four overarching dimensions for capturing social scientists' data practices, namely: 1) data characteristics, 2) perceived technical infrastructure, 3) perceived organizational context, and 4) individual characteristics. To ensure that the instrument can be applied in real and practical terms, we conduct a case study by collecting responses from 93 early-career social scientists at two research universities in the Pittsburgh Area, U.S. The results suggest that there is no significant difference, in general, among scholars who prefer quantitative, mixed method, or qualitative research methods in terms of research activities and data-sharing practices. We also confirm that there is a gap between participants' attitudes about research openness and their actual sharing behaviors, highlighting the need to study the 'barrier' in addition to the 'incentive' of research data sharing. [ABSTRACT FROM AUTHOR]

We investigate the automatic assignment of research methods to journal articles from the domain of Social Sciences. We employ Computer Science and Computational Linguistics methodology to perform this automatic assignment of metadata. The multi-label classification system we present uses only abstracts and titles of journal articles as input. Our best system is able to assign the important research methods empirical and quantitative empirical with F-scores of 0.67 and 0.68. These research methods are in the focus of many recent manual analyses of publications databases. Our classification approach could be applied to automatically analyze large publications databases and databases of bibliographic references according to the use of empirical and quantitative empirical methods. [ABSTRACT FROM AUTHOR]

Citation in academic articles is an important expression of knowledge flow between different disciplines. Analysis of citation content of references from different disciplines can help scholars to understand the role of various disciplines in knowledge flow. This study identifies the discipline of references in academic articles, and then explores the distribution pattern, including cited frequency and cited position (different type of section), of citation content of these references from different disciplines. Finally, we conclude that distribution patterns of different disciplines are different in knowledge flow. Although most references come from natural science, the humanities and social sciences still play an important role in the introduction and background. Basic disciplines like Mathematics are the main providers of methods, and some disciplines relevant to the research topic, like Nursing and Medicine in PLOS, provide more support for the results part of articles. [ABSTRACT FROM AUTHOR]

In this paper we describe an analysis inspired by institution theory on the collection development of social sciences data ar‐ chives. The theory introduces three dimensions that together support enduring social practices, i.e., regulative, normative, and cultural‐cognitive dimensions. We use the concepts to understand the nature and the relationships among the observed prob‐ lems in a case archive so as to better describe and understand the problems and possible solutions. [ABSTRACT FROM AUTHOR]

This study investigated how researchers in criminology dealt with their research data and explored the potential factors that would influence their willingness to share and reuse others' research data. Our findings unveiled three factors, trust, contract, and value, deeply rooted in researchers' attitudes and their data sharing and reuse patterns and behaviors. Through comprehending their concern behind sharing and reusing research data, we seek crucial insights that could be beneficial in developing a criminological research data repository, further consolidating the research data infrastructure in social science. Sharing and reusing data can advance scientific research and provide innovative possibilities for practice in criminology (e.g., new correctional methods, new crime prevention policies), providing sustained and thriving energy for the field. [ABSTRACT FROM AUTHOR]

The widespread use of artificial intelligence (AI) in many domains has revealed numerous ethical issues from data and design to deployment. In response, countless broad principles and guidelines for ethical AI have been published, and following those, specific approaches have been proposed for how to encourage ethical outcomes of AI. Meanwhile, library and information services too are seeing an increase in the use of AI‐powered and machine learning‐powered information systems, but no practical guidance currently exists for libraries to plan for, evaluate, or audit the ethics of intended or deployed AI. We therefore report on several promising approaches for promoting ethical AI that can be adapted from other contexts to AI‐powered information services and in different stages of the software lifecycle. [ABSTRACT FROM AUTHOR]

This is a SIG‐KM sponsored panel presented by members of the SIG‐KM officer team. First, the panel will overview their experience in knowledge management (KM) as scholars and scholar‐practitioners. They will briefly discuss their career development successes and hurdles as a roadmap for others to follow. Second, the panel will discuss career pathways for KM scholars and scholar‐practitioners in a global knowledge economy. Finally, they will hold an open discussion with audience members to share their experiences, expectations and hopes for the KM and the broader field of information science. [90 minute session]. [ABSTRACT FROM AUTHOR]

Data sharing and reuse practices in social sciences have changed in the past few decades with the continuing development of cyber‐infrastructures. However, little is known about how such practices chronically change over time. Via the lens of 35 years' worth of archived data on the world's largest social science data infrastructure, ICPSR, this study aims to reveal data characteristics (e.g., archived data themes and temporal distribution) that shape and represent the trend of social science data sharing and reuse. After a preliminary analysis on metadata of 10,362 studies and 159,616 associated citation records, an upward trend is found regarding the number of studies archived on ICPSR and their citation counts. We also report problems with metadata standards and the challenges of reusing data derived from these studies. Our results can be a cornerstone to investigate the roles of ICPSR as a research data infrastructure within the context of open science. [ABSTRACT FROM AUTHOR]

ABSTRACT The poster will present a summary of the arguments and topics raised in protest and support letters against the forthcoming closure of the Department for Information Science at the University of Duesseldorf, Germany. Case study-like this will shed light on how peers and stakeholders perceive the role and relevance of information science in general as well as the contribution of the Duesseldorf Department in particular. The poster aims, however, at providing a historical description on the actions taken and the arguments made. It will rather present indicators than significant evidence about perceptions of information science. The results of the small-scale topical analyses of the support letters, tweets, and comments to an online petition reveal that typical fields like information retrieval and knowledge management as well as skills like research or assessment of information are seen as assets of information scientists. However, popularizing the benefits of and - along with it - establishing information science as main subject within the (information) society is still due. [ABSTRACT FROM AUTHOR]