Text Mining for Big Data Analysis in Financial Sector: A Literature Review

Big data technologies have a strong impact on different industries, starting from the last decade, which continues nowadays, with the tendency to become omnipresent. The financial sector, as most of the other sectors, concentrated their operating activities mostly on structured data investigation. However, with the support of big data technologies, information stored in diverse sources of semi-structured and unstructured data could be harvested. Recent research and practice indicate that such information can be interesting for the decision-making process. Questions about how and to what extent research on data mining in the financial sector has developed and which tools are used for these purposes remains largely unexplored. This study aims to answer three research questions: (i) What is the intellectual core of the field? (ii) Which techniques are used in the financial sector for textual mining, especially in the era of the Internet, big data, and social media? (iii) Which data sources are the most often used for text mining in the financial sector, and for which purposes? In order to answer these questions, a qualitative analysis of literature is carried out using a systematic literature review, citation and co-citation analysis

The American Literature Scholar in the Digital Age

Essays reflecting on the development of the first wave of digital American literature scholarshi

Text mining and natural language processing for the early stages of space mission design

Final thesis submitted December 2021 - degree awarded in 2022A considerable amount of data related to space mission design has been accumulated since artificial satellites started to venture into space in the 1950s. This data has today become an overwhelming volume of information, triggering a significant knowledge reuse bottleneck at the early stages of space mission design. Meanwhile, virtual assistants, text mining and Natural Language Processing techniques have become pervasive to our daily life. The work presented in this thesis is one of the first attempts to bridge the gap between the worlds of space systems engineering and text mining. Several novel models are thus developed and implemented here, targeting the structuring of accumulated data through an ontology, but also tasks commonly performed by systems engineers such as requirement management and heritage analysis. A first collection of documents related to space systems is gathered for the training of these methods. Eventually, this work aims to pave the way towards the development of a Design Engineering Assistant (DEA) for the early stages of space mission design. It is also hoped that this work will actively contribute to the integration of text mining and Natural Language Processing methods in the field of space mission design, enhancing current design processes.A considerable amount of data related to space mission design has been accumulated since artificial satellites started to venture into space in the 1950s. This data has today become an overwhelming volume of information, triggering a significant knowledge reuse bottleneck at the early stages of space mission design. Meanwhile, virtual assistants, text mining and Natural Language Processing techniques have become pervasive to our daily life. The work presented in this thesis is one of the first attempts to bridge the gap between the worlds of space systems engineering and text mining. Several novel models are thus developed and implemented here, targeting the structuring of accumulated data through an ontology, but also tasks commonly performed by systems engineers such as requirement management and heritage analysis. A first collection of documents related to space systems is gathered for the training of these methods. Eventually, this work aims to pave the way towards the development of a Design Engineering Assistant (DEA) for the early stages of space mission design. It is also hoped that this work will actively contribute to the integration of text mining and Natural Language Processing methods in the field of space mission design, enhancing current design processes

Sustainability, Digital Transformation and Fintech: The New Challenges of the Banking Industry

In the current competitive scenario, the banking industry must contend with multiple challenges tied to regulations, legacy systems, disruptive models/technologies, new competitors, and a restive customer base, while simultaneously pursuing new strategies for sustainable growth. Banking institutions that can address these emerging challenges and opportunities to effectively balance long-term goals with short-term performance pressures could be aptly rewarded. This book comprises a selection of papers addressing some of these relevant issues concerning the current challenges and opportunities for international banking institutions. Papers in this collection focus on the digital transformation of the banking industry and its effect on sustainability, the emergence of new competitors such as FinTech companies, the role of mobile banking in the industry, the connections between sustainability and financial performance, and other general sustainability and corporate social responsibility (CSR) topics related to the banking industry. The book is a Special Issue of the MDPI journal Sustainability, which has been sponsored by the Santander Financial Institute (SANFI), a Spanish research and training institution created as a collaboration between Santander Bank and the University of Cantabria. SANFI works to identify, develop, support, and promote knowledge, study, talent, and innovation in the financial sector

Study on open science: The general state of the play in Open Science principles and practices at European life sciences institutes

Nowadays, open science is a hot topic on all levels and also is one of the priorities of the European Research Area. Components that are commonly associated with open science are open access, open data, open methodology, open source, open peer review, open science policies and citizen science. Open science may a great potential to connect and influence the practices of researchers, funding institutions and the public. In this paper, we evaluate the level of openness based on public surveys at four European life sciences institute

Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions

Artificial Intelligence (AI) is increasingly adopted by organizations to innovate, and this is ever more reflected in scholarly work. To illustrate, assess and map research at the intersection of AI and innovation, we performed a Systematic Literature Review (SLR) of published work indexed in the Clarivate Web of Science (WOS) and Elsevier Scopus databases (the final sample includes 1448 articles). A bibliometric analysis was deployed to map the focal field in terms of dominant topics and their evolution over time. By deploying keyword co-occurrences, and bibliographic coupling techniques, we generate insights on the literature at the intersection of AI and innovation research. We leverage the SLR findings to provide an updated synopsis of extant scientific work on the focal research area and to develop an interpretive framework which sheds light on the drivers and outcomes of AI adoption for innovation. We identify economic, technological, and social factors of AI adoption in firms willing to innovate. We also uncover firms' economic, competitive and organizational, and innovation factors as key outcomes of AI deployment. We conclude this paper by developing an agenda for future research

Trauma Innovations: MDMA as a Treatment Intervention for PTSD

Aims: To examine the evidence displayed across 3 distinct communities (popular, scientific, & clinical) in conjunction with the use of MDMA-AP as an intervention for PTSD. Method: A mixed method synthesis of qualitative and quantitative research. Data Sources: Four databases were searched [1980-Present] for MDMA & PTSD and/or Mithoefer, et al. 2010 specific scientific literature providing forty-two randomly selected articles; YouTube was searched specifically targeting the same criteria to provide forty-two randomly selected videos; 201 LICSW’s from Minnesota were also surveyed. Results: From the three datasets, three common themes emerged: (1) attitudes specifically geared toward MDMA-AP; (2) effusive or willful language; and (3) gaps in the research. Conclusions: Scientific literature is neutral to somewhat supportive of more study of MDMA-AP; primary source videos consider the topic highly newsworthy and are generally supportive of more study; LICSWs are supportive of the idea of further study of MDMA-AP

An Analysis of the Evolving Intellectual Structure of Health Information Systems Research in the Information Systems Discipline

The rapid evolution of health information systems (Health IS) research has led to many significantcontributions. However, while the Health IS subset of information systems (IS) scholarship hasconsiderably grown over the past two decades, this growth hasled to questions regarding the currentintellectual structure of this area of inquiry. In an effort to more fully understand how Health ISresearchhas contributed to the IS discipline, and what this may mean for future Health IS researchin the IS domain, we conduct an in-depth evaluation of Health IS research published in mainstreamIS journals. We apply citation analysis, latent semantic analysis (LSA), and social network analysis(SNA) to ourdata setof Health IS articles in order to: (1) identify Health IS research themes andthematic shifts, (2)determine which Health IS research themes are cohesive (versus disparate), (3)identify which Health IS research themes are central (versus peripheral), (4) clarify networks ofresearchers (i.e., thought leaders) contributing to these research themes, and(5) provide insights intothe connection of Health ISresearchto its reference disciplines. Overall, we contribute a systematicdescription and explanation of the intellectual structure ofHealth ISresearchand highlight how theexisting intellectual structure of Health ISresearchprovides opportunities for future research