Traditional citation analyses use quantitative methods only, even though there is meaning in the sentences containing citations within the text. This article analyzes three citation meanings: sentiment, role, and function. We compare citation meanings patterns between fields of science and propose an appropriate deep learning model to classify the three meanings automatically at once. The data comes from Indonesian journal articles covering five different areas of science: food, energy, health, computer, and social science. The sentences in the article text were classified manually and used as training data for an automatic classification model. Several classic models were compared with the proposed multi-output convolutional neural network model. The manual classification revealed similar patterns in citation meaning across the science fields: (1) not many authors exhibit polarity when citing, (2) citations are still rarely used, and (3) citations are used mostly for introductions and establishing relations instead of for comparisons with and utilizing previous research. The proposed model’s automatic classification metric achieved a macro F1 score of 0.80 for citation sentiment, 0.84 for citation role, and 0.88 for citation function. The model can classify minority classes well concerning the unbalanced dataset. A machine model that can classify several citation meanings automatically is essential for analyzing big data of journal citations.

The characterization of digital databases is needed to make it easier for academics to identify scientific literature properly and efficiently. This literature review intends to provide characterizations and descriptions related to research trends, methods and coverage fields studied in research related to the scientific database of scientific literature from around 2007 to the present (January 2019). By applying the specified inclusion and exclusion criteria, 54 relevant studies were chosen to be studied further. The systematic literature review method was applied in this study to analyze and identify previous studies related to this topic. Based on the selected primary literature there is an increasing trend of studies related to the scientific database of scientific literature. In addition, we can see that there are four of the most influential and influential publication journals related to this topic, namely the Journal of Informetrics, Journal of Cleaner Production, Asian Social Science and Journal of Academic Librarianship which are characterized by high levels of productivity issues related to the topics studied and SJR values rank is in the range Q1. Most of the studies were conducted on Scopus digital database (41%), Web of Sciences (WoS) 38% and Google Scholar (GS) 13% and the rest spread in other publication journals. The results of this study also identified that Scopus is a scientific database which has the most varied coverage fields compared to other digital database scientific literature. WoS is a digital database of scientific literature that has proven to have a paper with a higher impact factor than others. GS has the predicate digital database with the largest collection level. ABSTRAK Karakterisasi basis data digital perlu dilakukan, supaya dapat mempermudah para akademia melakukan identifikasi terhadap literatur ilmiah dengan tepat dan efisien. Tinjauan literatur ini bermaksud memberikan karakterisasi dan gambaran terkait tren riset, metode, dan coverage fields yang dikaji dalam penelitian terkait basis data digital literatur ilmiah pada kisaran tahu 2007 hingga saat ini (Januari 2019). Kriteria inklusi dan ekslusi yang telah ditetapkan, terpilih sebanyak 54 kajian yang relevan untuk dipelajari lebih lanjut. Metode tinjauan pustaka sistematis diterapkan dalam kajian ini untuk menganalisis dan mengidentifikasi kajian-kajian terdahulu terkait topik ini. Berdasarkan literatur primer yang dipilih diketahui terjadi tren peningkatan kajian terkait basis data digital literatur ilmiah. Selain itu, teridentifikasi terdapat empat jurnal publikasi paling berdampak dan berpengaruh terkait topik ini, yaitu Journal of Informetrics, Journal of Cleaner Production, Asian Social Science dan Journal of Academic Librarianship yang ditandai dengan tingkat produktivitas terbitan terkait topik yang diteliti termasuk tinggi dan nilai SJR rank berada pada kisaran Q1. Sebagian besar kajian dilakukan pada basis data digital Scopus (41%), Web of Sciences (WoS) 38% dan Google Scholar (GS) sebesar 13% serta sisanya meny...

Scientific data repository has a main role in science because data can be reused, reproduced, and preserved in a long time. In Indonesia there is no institution that manage scientific data repository, generally they only manage publication such as books, journals and proceedings. This is because, most of research data is still managed by a researcher or research group. By using literature study and survey to the journal publisher, authors want to get an information on how to manage research data by publications. Furthermore, the result of literature study is compared to the survey result that produces an important point i.e journal publisher strongly agree to make a policy to the author to attach research data in every paper submitted. Most of journal publisher use Open Journal System (OJS) in managing journal articles, start from paper acceptance until paper publishing. Through this way, research data that attached will be automatically stored to the scientific data repository system based on Application Programming Interface (API). ABSTRAK Repositori data ilmiah memiliki peran penting dalam ilmu pengetahuan, karena data dapat digunakan kembali (reuse), direproduksi (reproduce), dan menjamin ketersediaan jangka panjang. Di Indonesia belum ada lembaga yang mengelola repositori data ilmiah, umumnya hanya mengelola publikasi dalam bentuk buku, jurnal, dan prosiding. Hal ini dikarenakan sebagian besar data penelitian masih dikelola oleh peneliti atau kelompok penelitian. Melalui studi pustaka dan survei kepada pengelola jurnal, penulis ingin memperoleh informasi bagaimana mengelola data penelitian melalui publikasi. Selanjutnya, analisis terhadap studi literatur dibandingkan dengan hasil survei yang menghasilkan poin penting diantaranya: pengelola jurnal sangat setuju untuk membuat kebijakan kepada penulis agar melampirkan data penelitiannya dalam setiap naskah yang dikirimkan. Sebagian besar penerbit jurnal menggunakan Open Journal System (OJS) dalam mengelola artikel jurnal, mulai penerimaan hingga artikel diterbitkan. Melalui mekanisme ini, data penelitian yang dilampirkan dalam setiap naskah akan tersimpan secara otomatis ke sistem repositori data ilmiah berbasis Application Programming Interface (API).

Introduction. Citation is the main indicator in research performance evaluation using the quantitative approach. There have been many criticisms of citations since they were used half a century ago, but they have not yet succeeded in bringing new concepts and methods. This paper aims to criticize and propose a new approach to citation analysis. Data Collection Method. A contemporary critical theory methodology was adopted as a framework to collect and analyze the data. Scientific publications related to citation analysis was collected from several databases such as Google scholar, Microsoft academic search, dan Garuda Ristekdikti. Analysis Data. Publications data were critically reviewed and analyzed narratively by using open coding. Results and Discussions. The results mapped the lack of citation analysis form various aspects: (1) criticism of the positivist paradigm which did not succeed in achieving its objectives, (2) criticism of methods that produce invalid results, and (3) criticism of ethical issues of the researcher and  bias in implementation. The proposed solution and recommendation is to change the citation analysis method from a simple measurement of bibliographic data to text and context analysis based on a computer science approach (machine learning techniques). Conclusion. This new method has the potential to be developed within the framework of quantitative in Science and Technology studies to overcome existing criticisms. Subsequent multidisciplinary studies are needed to lay a strong philosophical and technical foundation particularly in applying the in-text citation analysis method for evaluating research performance in accordance with the Indonesian context.