Kisti Institutional Repository
Not a member yet
7415 research outputs found
Sort by
Identification of Profane Words in Cyberbullying Incidents within Social Networks
Full text linkThe popularity of social networking sites (SNS) has facilitated communication between users. The usage of SNS helps users in their daily life in various ways such as sharing of opinions, keeping in touch with old friends, making new friends, and getting information. However, some users misuse SNS to belittle or hurt others using profanities, which is typical in cyberbullying incidents. Thus, in this study, we aim to identify profane words from the ASKfm corpus to analyze the profane word distribution across four different roles involved in cyberbullying based on lexicon dictionary. These four roles are: harasser, victim, bystander that assists the bully, and bystander that defends the victim. Evaluation in this study focused on occurrences of the profane word for each role from the corpus. The top 10 common words used in the corpus are also identified and represented in a graph. Results from the analysis show that these four roles used profane words in their conversation with different weightage and distribution, even though the profane words used are mostly similar. The harasser is the first ranked that used profane words in the conversation compared to other roles. The results can be further explored and considered as a potential feature in a cyberbullying detection model using a machine learning approach. Results in this work will contribute to formulate the suitable representation. It is also useful in modeling a cyberbullying detection model based on the identification of profane word distribution across different cyberbullying roles in social networks for future works
Content Analysis of the Facebook Pages of Selected Academic Libraries in Vietnam
Full text linkThis study explores Facebook use in Vietnamese academic libraries by analysing libraries' posts on their Facebook pages and library users' interaction with those posts. A total of 260 posts on four academic libraries' Facebook pages were examined using the content analysis method. The findings reveal that Facebook was mainly used to encourage reading and to transmit announcements. Most of the academic libraries published one post a week. The photo was the most frequent media type of libraries' posts and gained a higher level of interaction than other posts. According to the research results, the user engagement was low, and the user interaction with libraries' posts generally was in the form of reaction. The findings can help better understand Facebook use in Vietnamese academic libraries and may assist libraries in creating a plan for using Facebook more effectively
Word Embeddings-Based Pseudo Relevance Feedback Using Deep Averaging Networks for Arabic Document Retrieval
Full text linkPseudo relevance feedback (PRF) is a powerful query expansion (QE) technique that prepares queries using the top k pseudorelevant documents and choosing expansion elements. Traditional PRF frameworks have robustly handled vocabulary mismatch corresponding to user queries and pertinent documents; nevertheless, expansion elements are chosen, disregarding similarity to the original query's elements. Word embedding (WE) schemes comprise techniques of significant interest concerning QE, that falls within the information retrieval domain. Deep averaging networks (DANs) defines a framework relying on average word presence passed through multiple linear layers. The complete query is understandably represented using the average vector comprising the query terms. The vector may be employed for determining expansion elements pertinent to the entire query. In this study, we suggest a DANs-based technique that augments PRF frameworks by integrating WE similarities to facilitate Arabic information retrieval. The technique is based on the fundamental that the top pseudo-relevant document set is assessed to determine candidate element distribution and select expansion terms appropriately, considering their similarity to the average vector representing the initial query elements. The Word2Vec model is selected for executing the experiments on a standard Arabic TREC 2001/2002 set. The majority of the evaluations indicate that the PRF implementation in the present study offers a significant performance improvement compared to that of the baseline PRF frameworks
A Novel Method for Identifying Competitors Using a Financial Transaction Network
No full textIdentifying competitors is an essential first step in creating a competitive advantage to generate superior business performance. Diverse methods for competitor identification have been introduced in the literature, but financial transactions are overlooked in these models even though such transactions among firms, as the basic economic unit of interfirm business activities, contain critical information. This article proposes a novel method for the identification of firm-level competitors using a network constructed from financial transactions among firms.We propose network-theoretic similarity measures to quantify the resource similarity and market commonality between firms by considering both direct and indirect transactions in a transaction network. Then, based on the two dimensions, three types of competitors are identified with respect toafocalfirm:direct,potential,andindirect competitors. The proposed method is applied to toy network data and a real-world case that includes the financial transactions of firms in Korea in 2014
KISTI, 창립 20주년(통산 59주년) 기념식 개최
Full text link한국과학기술정보연구원(원장 김재수, 이하 KISTI)이 5월 19일 창립 20주년(통산 59주년)을 맞는다. 1962년 출범한 KISTI는 지난 2001년 산업기술정보원(KINITI)과 연구개발정보센터(KORDIC)가 통합하여 출범하였다.
3월 취임한 KISTI 신임 김재수 원장은 “과학기술인프라, 데이터로 세상을 바꾸는 KISTI”라는 비전 아래, “TRUST KISTI, 신뢰와 혁신”이라는 핵심가치와 이를 위한 추진전략으로 애자일(Agile), 디지털 전환(DX), ESG 경영을 제시했다
2021년 KISTI-NVIDIA GPU 해커톤 개최
Full text link한국과학기술정보연구원(원장 김재수, 이하 KISTI)은 엔비디아(CEO 젠슨 황, 이하 NVIDIA), OpenACC와 함께 2021년‘KISTI-NVIDIA GPU Hackathon’을 8월 25일부터 9월 1일까지 온라인으로 개최했다.
올해로 2회째를 맞는 이번 해커톤에는 대학·기업·기관 등 총 6개 팀이 참가하였으며, KISTI의 슈퍼컴퓨터 보조시스템인 GPU 클러스터(NEURON)를 활용하여 AI 연구개발, HPC 코드 가속화 등의 프로젝트를 수행했다
KISTI, 한국정보보호학회와 양자보안연구회 워크숍 개최
Full text link한국과학기술정보연구원(원장 김재수, 이하 KISTI)과 한국정보보호학회는 양자보안기술 글로벌 협력과 산업 활성화 전략을 위하여 9월 29일 KISTI 대전본원 키움관에서 2021년 양자보안연구회 워크숍을 개최한다. 이번 워크숍은 해외 양자보안 기술발전에 대비한 국내 산·학·연들의 대응 전략에 대한 행사로, 4개 세션으로 나눠 다양한 분야별 발표를 통해 양자키분배(QKD, Quantum Key Distribution), 양자내성암호(PQC, Post-Quantum Cryptography)에 대한 연구 현황과 기술 표준 동향을 알아볼 수 있다
국가오픈액세스플랫폼 브랜드 AccessON으로!
Full text link한국과학기술정보연구원(원장 김재수, 이하 KISTI)은 10월 8일 국가오픈액세스 플랫폼의 브랜드명을 기존 KOAR에서 AccessON(액세스온)으로 변경한다고 밝혔다
오픈 사이언스 확산을 위한 ‘건전한 학술활동’ 방안 찾는다
Full text link한국과학기술정보연구원(이하 ′KISTI′, 원장 김재수)은 오는 25일 ‘건전학술활동포럼’을 개최한다. 과학기술정보통신부, 한국과학기술단체총연합회가 후원하는 이번 포럼은 ‘오픈 사이언스 시대, 부실 학술출판의 쟁점과 대응 방안’을 주제로 최근 학술 생태계의 이슈로 등장한 ‘부실 학술지’에 대한 대응 방안을 모색하고 건전한 학술출판 문화를 조성하고자 마련됐다
