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This study investigated papers posted on bioRXiv. In 2013–19, 17,818 papers were published in academic journals, accounting for 40.67% of the total publication. Among them, the Web of Science (WoS) Core Collection recorded journals of 16,525 published papers, accounting for 92.74% of the total. The following conclusions can be drawn. (1) Results indicate scientists' attention to the preprint system. (2) A large number of papers still use traditional publishing as the ultimate goal. (3) Because the posted papers scrutinized in this study were published in journals with a high impact factor, they have attracted the attention of many scientists. Nevertheless, we believe that the preprint platform will play a greater role from the academic exchange perspective. [ABSTRACT FROM AUTHOR]

This paper studied whether opening up review reports benefits science in terms of citations, by taking Nature Communications as an example. To address these questions, we extracted 3,500 papers published in Nature Communications in 2016 and 4,326 papers in 2017 and retrieved their three‐year citations since publication in the Web of Science database. By applying the Matching method, we constructed an observation group including 1,726 open peer review (OPR) papers and a control group including 1,726 non‐OPR counterparts. The results of the paired sample t‐test showed no significant difference between the OPR and non‐OPR papers. We conclude that opening up peer review reports did not benefit papers in Nature Communications in terms of citations. We further examined whether the length, the rounds or the lexical diversity of the review report contributed to the paper's citations, through regression analysis. As a result, we found that longer comments, more rounds of review and the more diversified words did not contribute to the citations of the OPR papers in Nature Communications. Further research covering more OPR journals is required to justify the benefits of OPR. [ABSTRACT FROM AUTHOR]

Argumentation structure within the content of scientific paper is the fundamental for proving scientific findings. Constructing the argumentation graph is an effective way to realize the visualization of argumentation structure and help users quickly understand the logical of papers. This study presents the method for constructing argumentation graph of scientific papers, includes an ontology for describing the scientific papers' argumentation structure, a process for deep semantic annotation and a mapping protocols for transforming the annotation results into graph structure by using Neo4J. The method was applied to construct an argumentation graph and the argumentation process retrieval was also realized. The result suggest that the argumentation graph could be benefit for the argumentation visualization and strategic reading of scientific papers. [ABSTRACT FROM AUTHOR]

Online bibliographic databases have enabled new research through which bibliographic records are analyzed as data about science. Within these records, the acknowledgements sections of papers are often used to draw conclusions about funding support for published research. While acknowledgements and funding statements can be informative for research and policy development, this poster adds to a body of literature that highlights limitations of funding data for scientometric and policy research, using evidence gathered from a questionnaire of authors of astronomy journal articles. The study shows that only 71.4% of a sample of authors of papers tied to NSF grants through acknowledgements reported in the survey that NSF funded the research presented in the respective papers. A brief analysis of the questionnaire followed by recommendations and considerations for further research are presented. The discrepancy in reporting appears to indicate that funding streams can be fluid and not always apparent to authors, overall raising the question of what sorts of research should be addressed with funding statements, where conceptually tying a paper directly to a grant is not straightforward. [ABSTRACT FROM AUTHOR]

Citation content Analysis is very useful to reveal the nature of citations among scientific papers. However, most of previous studies had been done only from the side of citing papers and ignored the side of cited papers. We proposed a similarity‐based unsupervised citation text identification method and a ranking‐based supervised cited text identification method. Based on the identified citation and cited texts, we performed a fine‐grained citation analysis and found there was a difference in the cited texts between the citing papers in different disciplines. [ABSTRACT FROM AUTHOR]

ABSTRACT Citation is an important measurement in science which provides valuable clues to the historical development and trend forecast of science. However, the evolution of citation structure remains poorly understood despite long-period and frequent use of citation counts for assessment purposes within scientific community. We observe citation structure from a cascade perspective and construct a large and long-range citation graph based on real data. Two metrics are used to quantify the structural virality and cascade size. Preliminary results show that (1) age plays an important role for the evolution of citation cascades; (2) average depth tends to be influenced by both lifespan and the whole volume of scientific literature and grows much slower than cascade size; (3) there exists a stable positive relationship between average depth and cascade size, and it seems that an ultimate status exists where most papers eventually have large values for both metrics. [ABSTRACT FROM AUTHOR]

This study examines the relation between acceptance times in preprint publishing and journal publishing. Specifically, we investigated the association between a paper's posting time to bioRχiv, a preprints server, and journal articles' peer‐review and acceptance time for PLOS ONE. So far, of the total papers published in 1,626 academic journals, the average publication rate of those posted in bioRχiv is 40.67%. Meanwhile, PLOS ONE was the journal that published more papers. Analysis of peer‐review and acceptance time of papers published in journals via preprints showed the time these papers are posted in relation to these intervals. The median of the peer‐review and acceptance time of the journal submission date that was later than the date of first posting to bioRχiv was 110.00 days, and in the reverse case, it was 139.50 days. Posting to the preprint server before journal submission shows a better order than vice versa. This study provides us a good understanding of the peer‐review process. It also gives us good insights into optimizing this process, which would then facilitate paper publication and knowledge dissemination. [ABSTRACT FROM AUTHOR]

Peer review can evaluate the quality of academic articles involving the evaluation of some aspects, e.g., methodology, experiment, and aspects are usually the critical sections, substance and properties of the article concerned by reviewers. Previous research on content mining of peer review did not distinguish the round of reviews. Detecting differences peer review comments among different rounds can help us to understand the focus change of the reviewers in the different rounds. This paper takes the Nature Communications as an example to build the corpora of peer reviews in multiple rounds. We correlate review rounds and citations and extract aspects from the corpora to analyze the round characteristics of review comments. We find that there is no significant correlation between the review rounds and the citations frequency, but when the number of rounds is within 1–3, there is a weak positive correlation between the review rounds and citations. Additionally, the reviewers tend to pay more attention to the results analysis and the significance of the work firstly, and then they will focus on the details of the article, such as diagrams. This study can provide new ideas for peer review mining and the application of bibliometrics. [ABSTRACT FROM AUTHOR]

Research trend detection is an important topic for scientific researchers. Future work sentences (FWS), as direct descriptions of future research, aren't fully utilized in research trend detection. Therefore, this article uses FWS to investigate research trends of different tasks in a particular domain. Taking the conference papers in the natural language processing (NLP) field as our research objects, we obtain the FWS in each paper to build the corpus and classified them into 6 main types. After that, the task of each paper is annotated, and a task system with 29 categories is constructed to compare the FWS in different tasks. The results show that the proportion of method mentioned in FWS is the highest, and different tasks focus on different FWS types: emerging tasks need more resources, while mature tasks prefer method and application. This study provides researchers a reference to understand the research trend of specific tasks and is helpful to compare different tasks. [ABSTRACT FROM AUTHOR]

Retraction removes seriously flawed papers from the scientific literature. However, even papers retracted for scientific fraud continue to be cited and used as valid after their retraction. Retracted papers are inadequately identified on publisher pages and in scholarly databases, and scholars' personal libraries frequently contain retracted papers. To address this, we are developing a tool called ReTracker (https://github.com/nikolausn/ReTrackers) that automatically checks a user's Zotero library for retracted articles, and adds retraction status as a new metadata field directly in the library. In this paper, we present the current version of ReTracker, which automatically flags retracted articles from PubMed. We describe how we have iteratively improved ReTracker's matching performance through its initial two versions. Our tests show that the current version of ReTracker is able to flag retracted articles from PubMed with high precision and recall, and to distinguish retracted articles from articles about retraction. In its current state, ReTracker can actively and automatically bring retraction metadata into Zotero, and in future work we will test its usability with scholars. [ABSTRACT FROM AUTHOR]

As data becomes omnipresent in the scientific system, a new academic genre aiming to describe data objects (data papers) and the venue to publish these articles (data journals) gradually emerged from the end of the 2000s. However, it is largely unknown how much these scientific outputs are indexed in scientific databases, which has greatly prevented them from being thoroughly studied in large‐scale, quantitative studies. This poster presents our preliminary efforts to address this gap, by compiling a list of data journals that primarily accept data papers (i.e., exclusively data journals) and examining their presence in four major scientific databases. Our results indicate that exclusively data journals are comprehensively indexed in Crossref and Dimensions, two relatively new scientific databases, which can be used to conduct future studies on data papers and journals. The next steps of our project are also discussed in this poster. [ABSTRACT FROM AUTHOR]

This paper presents and evaluates a collaborative attribution strategy based on six authorship attribution schemes representing the two main paradigms used in authorship studies. Based on very frequent words as features, the classical paradigm (or similarity-based methods) proposes to compute an intertextual distance between the disputed text and the different author profiles (concatenation of their writings). As a second paradigm, we can apply different machine learning schemes such as the naïve Bayes, and the support vector machines (SVM). As an evaluation corpus, we have used The Federalist Papers, a wellknown collection in authorship attribution. During our evaluation, we have tried to follow the recommendations and the best practices known to assess the various attribution schemes. The evaluation shows that, in the two paradigms, we can find effective attribution schemes. But when combining these individual results using a vote aggregation method, the final collaborative decision is always correct and robust. Moreover, to indicate the degree of belief attached to the combined attribution, we can consider the percentage of votes obtained by each possible assignment. When analyzing the output given by the individual attribution schemes, we also found that the provided information is difficult to interpret, at least, for the end-user. [ABSTRACT FROM AUTHOR]

This study analyzes the level of interdisciplinarity and interspecialty of highly cited papers. We distinguish research referring to different disciplines (referred to as "interdisciplinarity") and research referring to different specialties of the same discipline (referred to as "interspecialty"). The results indicate that: (1) interspecialty research, has a greater impact on science development than intradisciplinary (or intraspecialty) research for most specialties and disciplines; (2) interdisciplinary research plays a more important role in Natural Sciences and Engineering than in Social Sciences and Humanities; and (3) interdisciplinary research is becoming more important in science either at the specialty or discipline level. [ABSTRACT FROM AUTHOR]

ABSTRACT Scientific software is as important to scientific studies as raw data. Yet, attention to this genre of research data is limited in studies on data reuse, citation, and metadata standards. This paper presents results from an exploratory study that examined how scientific software's reuse information is presented in the current citation practice and natural language descriptions in research papers. We selected LAMMPS, popular simulation software used in material science, for this study. Both descriptive metadata elements and the types of reuse are examined from a sample of 400 research papers. The results indicate that both descriptive metadata elements and reuse types about LAMMPS are presented in incomplete and inconsistent ways, and this interferes with the values of scientific software, as a type of research data. Our findings necessitate future studies on the metadata standards to facilitate the identification of information related with scientific software reuse. [ABSTRACT FROM AUTHOR]

Researchers in academia and industry face a deluge of data in our digital world. In this paper, we investigate a novel problem, query-centric scientific topic evolution. Using heterogeneous graph mining techniques we construct a topic evolution tree (TET) from massive collections of scientific publications, enabling students and researchers to explore the foundation of research topics outside their specialization. Prior research has focused mainly on citation relationships; in this study we employed multiple types of relationships, including authorship, citation, publishing venue, and the contributions authors, papers, and venues have made to a specific topic. We examine multiple restricted meta-paths in constructing a TET covering topics from the MeSH vocabulary for biomedical research. [ABSTRACT FROM AUTHOR]

This paper is based on the Web of Science database and takes advantage of CiteSpace, a scientometric software, to conduct visualization analyses. It is found that privacy issues in data ethics have reached the research peak in the past two years. The findings of this paper are that the current global research in this field is characterized by three different periods and multidisciplinary perspectives. And the hotspots of this field are relatively concentrated and gradually deepened. Besides, the research in this field has moved from the theoretical stage to the practical application stage. This paper attempts to present the scientific knowledge structure, patterns and distribution of privacy issues in data ethics, exploring the global frontier hotspots, providing inspiration and experience for Chinese academic research and industry practice in data ethics. [ABSTRACT FROM AUTHOR]

The growth of digital curation as a field of research has exploded in recent years. However, little work has been directed at the study of changes in the field, and no effort has been made to identify predominant trends and gaps in the research literature. This study examines the International Journal of Digital Curation (IJDC) over an eight-year period from its inception in 2006 to 2013. A total of 219 papers published in the IJDC was examined in terms of paper productivity, keywords in abstracts, authorship, citations received, and funding received. The preliminary results of this study found a steady upward trend in paper productivity. An overwhelming number of papers were coauthored papers from the United Kingdom and United States. The majority of the papers were cited more than once. Half the papers were supported by grants from federal government agencies. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper proposes a 'rough co-citation', which is a measure of relationship to expand co-citation networks so as to include new relevant documents. A rough co-citation relationship is a linkage between a pair of documents which are cited by two other documents in a similar citation context. The linkage strength of a rough co-citation relationship may be weaker than the original co-citation relationship, because a rough co-citation relationship is determined by citations in two separate documents. Rough co-citation linkages, however, may yield new relevant documents that are not identified by the original co-citation linkages. For example, the rough co-citation can identify relevant documents that are published after the citing document of the original co-citation becomes public. This study conducted IR experiments to evaluate the search performances of retrieval methods using the co-citation networks expanded by the rough co-citation relationships. Specifically, the random walk with restart, which is one of the latest graph search algorithms, is applied to the expanded and original co-citation networks. Scores of the normalized discounted cumulative gain (nDCG@K) are then compared. The results indicate that the search performance of the method using the expanded network outperforms a baseline method using the original network. [ABSTRACT FROM AUTHOR]

ABSTRACT In this poster, we describe partial findings from a larger study that explored the co-first and co-corresponding author phenomenon in two biomedical research areas, pharmacy and anesthesia. The top 10 journals in the two areas by the five-year impact factor as listed in 2013 JCR were used for the paper sources. A total of 17802 pharmacy papers and 35801 anesthesia papers were included in the analyses. Each paper was manually examined to identify the co-first and co-corresponding author papers. In this poster, we will show the distributions of the paper numbers and percentages of the co-first and co-corresponding papers over twenty years (1995-2014), the distributions of author numbers sharing the co-first and co-corresponding authorship, and the combinations and distributions of the authors' byline positions. [ABSTRACT FROM AUTHOR]

In recent years the number of individuals struggling with mental illness has increased, and traditional mental health services are now considered insufficient under the current circumstances which has prompted researchers to develop new approaches for mental healthcare. Social media usage is growing, and it is been utilized to help provide additional insight on mental health by using the information shared by individuals, as well as data taken from their social media activity. While this approach may provide a unique and effective perspective for mental health services, it is critical that privacy risks and protections are considered in the process. Social media services collect, process, and stores a substantial amount of information about its users and how that information is shared as well as what type of predictions are made may pose serious privacy concerns. This study aims to understand how privacy is addressed and emphasized during the process of using social media data for mental healthcare by constructing a systematic review on previous scholarly papers related to the topic. Solove's taxonomy of privacy is used to evaluate these publications privacy considerations and to demonstrate the privacy risks that may arise when social media data is used for mental health. [ABSTRACT FROM AUTHOR]

Treating all citations in a reference list equally is one of the common practices of citation analysis that have long been criticized. The increasing availability of digital full-text documents now makes it feasible to weigh citations in various ways, e.g., by their frequency or location in the text. In this paper we report preliminary results of a comparison of author citation weighing schemes based on in-text citation frequency, and the citation impact patterns that emerge from them in the field of library and information science. [ABSTRACT FROM AUTHOR]

Text mining is a research method that uses interdisciplinary techniques to identify patterns and trends in unstructured data and can be used to detect research trends and developments in various fields. Thus, this study attempts to identify research trends in the issue of privacy concern (PC), focusing on the differences between the first two decades of the 21st century. This is done by applying an automated textual analysis tool (Voyant Tools) on a vast corpora of academic papers conducted on this field. We found that while the first examined decade of PC research focused on commerce and marketing issues, there was much more research emphasis on the social dimension of privacy in the second decade. This difference was explained by the technological developments that were prominent in the respective decades. The research provided support for the use of textual analysis of academic literature as a tool to identify research trends in various fields, including technologically‐oriented fields. [ABSTRACT FROM AUTHOR]

Publications represent the most tangible products of research and scholarly communication. Growing pressures placed on researchers to increase their publication counts may encourage them to publish shorter papers, so that more publications may be generated from the same project and program. Is this the case? Furthermore, do shorter papers garner the same impact as longer papers as measured by the citations received? This research examines the relationship between article length and citations received by articles published in three prominent top biomedical research journals over the lifetime of the journals. The study reveals that instead of getting shorter, articles in these journals are getting longer over time. Longer articles in these journals, on average, attract more citations, and are therefore considered more impactful. [ABSTRACT FROM AUTHOR]

Research trends are the keys for researchers to decide their research agenda. However, only few works have tried to quantify how scholars follow the trends. This paper addresses this problem by proposing a novel measurement for quantifying how a scientific entity (paper or researcher) follows the hot topics in a research field. Specifically, the topic evolution and papers are vectorizing by dynamic topic modeling. Then the degree of hotness tracing is explored from three different perspectives: mainstream, short‐term direction, long‐term direction. Papers and researchers in the field of Computer Vision from 2006 to 2017 were selected to evaluate our method. Further study will show the results of topic evolution patterns and researchers' clusters. [ABSTRACT FROM AUTHOR]

Database maintenance and migration are critical but under‐supported activities in libraries, archives, museums (LAMs), and other scholarly spaces. Existing guidelines for digital curation rarely account for the maintenance needed to keep digital curation infrastructures functioning over time. Though many case studies have been published describing individual instances of migration, there has been little generalizable research done in this area. Thus, it is challenging to understand overall trends or best practices in this space. We bridge this gap by conducting an integrative literature review of papers describing database migrations and maintenance in LAMs and other scholarly contexts. By qualitatively coding 75 articles from 58 publication venues, we identify common motivations for database migrations and maintenance actions. We find that databases are migrated to support changing user needs as well as to ward off technological obsolescence; we also find that common challenges include schema crosswalking and a need for data cleaning. Practitioners describe community collaboration as key in surmounting these challenges. Through this integrative review, we build a base for further best practices development and identify a need to better model database curation as part of the digital curation lifecycle. [ABSTRACT FROM AUTHOR]

Publication is a vital part of the career of any researcher. There is an increasing awareness that the presented gender of authors can impact their acceptance at competitive venues, and also influence the support they receive to participate in conferences. Similarly, geography and the associated costs of travel to conferences also impact the likelihood a potential author will submit to a conference. Recent research has examined these impacts in the context of related disciplines within computing and considered the gender profile of reviewers and authors at the iConference. This paper examines the impact of gender and geography on the representation of authors in the ASIST Annual Meeting and the JASIST journal. Through an evaluation of the first authors of accepted papers or articles, we assess the relative representation of genders, and the degree to which conference location impedes or enables authors from different regions. Our findings provide a foundation for the information science community to work towards better representation of female and international authors. [ABSTRACT FROM AUTHOR]

We carried out an experiment to extract ecological‐restoration‐technology‐related entities (i.e., entities related to the fragile ecological remediation technology of desertification, rocky desertification, water and soil erosion control areas, place entities, and time entities related to the technology performed,) from full‐text documents published in the CNKI from 1978 to 2017. Based on the extraction of the time entities, place entities, and fragile ecological remediation technology entities, we analyzed the technologies with the greatest potential from among China's fragile ecological restoration technologies using the category clustering of fragile ecological restoration technologies with LDA and the place distribution and evolution of fragile ecological treatment technologies. This research shows that the proposed Bi‐LSTM+CRF combined with the feature‐based named entity knowledgebase can be used to perform geographical knowledge discovery from text, and it has has good prospects for applications in intelligence analysis based on text mining. [ABSTRACT FROM AUTHOR]

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 proposes an indicator for measuring the level of commitment to academic journals. The indicator is demonstrated on a sample of core LIS‐journals. By monitoring authorship patterns over a 20‐year period, it is shown that some journals have a higher frequency of returning authors than others, consequently showing a larger degree of community commitment. The paper discusses how the indicator may be applied when studying factors influencing researchers' journal selection decisions. [ABSTRACT FROM AUTHOR]

Manufacturing enterprises always generate, acquire, and transform large amount of information which flows across every link of their innovation process and value chain. Information flow is one of the basic conditions for information to be reproduced, utilized and value added. Unreasonable paths and transmission methods of information flow will lead to problems such as poor flow efficiency, low information sharing and even information silos, which will further restrict the R&D innovation and service upgrade. Optimizing information flow mechanisms and paths is a vital part for improving the innovation capability of manufacturing enterprises. In order to reflect the interactions, flow‐path differences and nonlinear laws among manufacturing enterprises' innovation units and to reveal relations between information‐flowing efficiency and innovation capabilities, the paper divides innovation activities of manufacturing enterprises into three phases, such as information acquisition, information transformation and information value addition based on the theory of innovation value chain, and puts forward a mathematical model of information absorption and transformation to ultimately reveal the mechanisms for information flow across inside and outside units. Further, the paper takes a non‐linear function for absorptive capacity based on level of experiential knowledge, continuous R&D intensity, and agent relation strength to quantify the information absorption and transformation process and takes index of innovation information amount and cumulative information amount to calculate innovation abilities and measure information value addition. Finally, the paper uses simulation tool to analyze the influencing factors of information absorption and transformation optimization. [ABSTRACT FROM AUTHOR]

This study is to investigate how citing behavior for a scientific article changes over time. A highly cited article is chosen to collect citation content from its 902 citing articles. Natural language processing and content analysis are adopted to encode citation content and complete the statistics of citation behavior. Citation content analysis indexes including citation mention, length, and location, are used to describe the changes of citation behavior over time. The experimental results show that there is correlation between citing time with most of the indexes and that citation mention and citation length are declining while the number of the citation co-occurrences is increasing. [ABSTRACT FROM AUTHOR]