Self Defense Module

Self Defense module is like a Smart Watch For Women .It has the potential to help women with technologies that are embedded. It is specially designed for women safety. It has a control button that will be used by women to inform nearby police when they are in danger. This watch directly gets connected to the satellite through GPS when activated. Then the location is transferred through the GSM and it is also provided with a system that produces 60 shockwaves in 1 second in emergency situations

Blogs as Infrastructure for Scholarly Communication.

This project systematically analyzes digital humanities blogs as an infrastructure for scholarly communication. This exploratory research maps the discourses of a scholarly community to understand the infrastructural dynamics of blogs and the Open Web. The text contents of 106,804 individual blog posts from a corpus of 396 blogs were analyzed using a mix of computational and qualitative methods. Analysis uses an experimental methodology (trace ethnography) combined with unsupervised machine learning (topic modeling), to perform an interpretive analysis at scale. Methodological findings show topic modeling can be integrated with qualitative and interpretive analysis. Special attention must be paid to data fitness, or the shape and re-shaping practices involved with preparing data for machine learning algorithms. Quantitative analysis of computationally generated topics indicates that while the community writes about diverse subject matter, individual scholars focus their attention on only a couple of topics. Four categories of informal scholarly communication emerged from the qualitative analysis: quasi-academic, para-academic, meta-academic, and extra-academic. The quasi and para-academic categories represent discourse with scholarly value within the digital humanities community, but do not necessarily have an obvious path into formal publication and preservation. A conceptual model, the (in)visible college, is introduced for situating scholarly communication on blogs and the Open Web. An (in)visible college is a kind of scholarly communication that is informal, yet visible at scale. This combination of factors opens up a new space for the study of scholarly communities and communication. While (in)invisible colleges are programmatically observable, care must be taken with any effort to count and measure knowledge work in these spaces. This is the first systematic, data driven analysis of the digital humanities and lays the groundwork for subsequent social studies of digital humanities.PhDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111592/1/mcburton_1.pd

Digital Literary and Cultural Studies: State of the Art and Perspectives

Over the last decade Digital Humanities has ceased being a “niche discipline” and have become a major phenomenon in academic and cultural debate. Significant scientific results and outcomes have been achieved, and fundamental research infrastructures have been realized. Despite these far-reaching outcomes, Digital Humanities still does not have a satisfactory influence in the traditional disciplinary fields. We need to find new methods to deal with cultural artifacts and texts. Amongst the many emerging research fields in the DH, two come forth as the most promising and interesting: Big Data and distant reading; Semantic Web and Linked Open Data. In my paper I will argue that Big Data in the Humanities, although very promising, have some critical issues, and I will propose the idea of a Semantic Cultural and Literary Web, a collaborative infrastructure based on ontology driven semantic annotation of primary resources

Digital Literary and Cultural Studies: State of the Art and Perspectives

Over the last decade Digital Humanities has ceased being a “niche discipline” and have become a major phenomenon in academic and cultural debate. Significant scientific results and outcomes have been achieved, and fundamental research infrastructures have been realized. Despite these far-reaching outcomes, Digital Humanities still does not have a satisfactory influence in the traditional disciplinary fields. We need to find new methods to deal with cultural artifacts and texts. Amongst the many emerging research fields in the DH, two come forth as the most promising and interesting: Big Data and distant reading; Semantic Web and Linked Open Data. In my paper I will argue that Big Data in the Humanities, although very promising, have some critical issues, and I will propose the idea of a Semantic Cultural and Literary Web, a collaborative infrastructure based on ontology driven semantic annotation of primary resources.Over the last decade Digital Humanities has ceased being a “niche discipline” and have become a major phenomenon in academic and cultural debate. Significant scientific results and outcomes have been achieved, and fundamental research infrastructures have been realized. Despite these far-reaching outcomes, Digital Humanities still does not have a satisfactory influence in the traditional disciplinary fields. We need to find new methods to deal with cultural artifacts and texts. Amongst the many emerging research fields in the DH, two come forth as the most promising and interesting: Big Data and distant reading; Semantic Web and Linked Open Data. In my paper I will argue that Big Data in the Humanities, although very promising, have some critical issues, and I will propose the idea of a Semantic Cultural and Literary Web, a collaborative infrastructure based on ontology driven semantic annotation of primary resources.

Methodological roadmapping: a study of centering resonance analysis

Purpose – This paper aims to map the creation and evolution of centering resonance analysis (CRA). This method was an innovative approach developed to conduct textual content analysis in a semi-automatic, theory-informed and analytically rigorous way. Nevertheless, despite its robust procedures to analyze documents and interviews, CRA is still broadly unknown and scarcely used in management research. Design/methodology/approach – To track CRA’s development, the roadmapping approach was properly adapted. The traditional time-based multi-layered map format was customized to depict, graphically, the results obtained from a systematic literature review of the main CRA publications. Findings – In total, 19 papers were reviewed, from the method’s introduction in 2002 to its last tracked methodological development. In all, 26 types of CRA analysis were identified and grouped in five categories. The most innovative procedures in each group were discussed and exemplified. Finally, a CRA methodological roadmap was presented, including a layered typology of the publications, in terms of their focus and innovativeness; the number of analysis conducted in each publication; references for further CRA development; a segmentation and description of the main publication periods; main turning points; citationbased relationships; and four possible future scenarios for CRA as a method. Originality/value – This paper offers a unique and comprehensive review of CRA’s development, favoring its broader use in management research. In addition, it develops an adapted version of the roadmapping approach, customized for mapping methodological innovations over time

SIWeb: understanding the Interests of the Society through Web data Analysis

The high availability of user-generated contents in the Web scenario represents a tremendous asset for understanding various social phenomena. Methods and commercial products that exploit the widespread use of the Web as a way of conveying personal opinions have been proposed, but a critical thinking is that these approaches may produce a partial, or distorted, understanding of the society, because most of them focus on definite scenarios, use specific platforms, base their analysis on the sole magnitude of data, or treat the different Web resources with the same importance. In this paper, we present SIWeb (Social Interests through Web Analysis), a novel mechanism designed to measure the interest the society has on a topic (e.g., a real world phenomenon, an event, a person, a thing). SIWeb is general purpose (it can be applied to any decision making process), cross platforms (it uses the entire Webspace, from social media to websites, from tags to reviews), and time effective (it measures the time correlatio between the Web resources). It uses fractal analysis to detect the temporal relations behind all the Web resources (e.g., Web pages, RSS, newsgroups, etc.) that talk about a topic and combines this number with the temporal relations to give an insight of the the interest the society has about a topic. The evaluation of the proposal shows that SIWeb might be helpful in decision making processes as it reflects the interests the society has on a specific topic

State of the art 2015: a literature review of social media intelligence capabilities for counter-terrorism

Overview This paper is a review of how information and insight can be drawn from open social media sources. It focuses on the specific research techniques that have emerged, the capabilities they provide, the possible insights they offer, and the ethical and legal questions they raise. These techniques are considered relevant and valuable in so far as they can help to maintain public safety by preventing terrorism, preparing for it, protecting the public from it and pursuing its perpetrators. The report also considers how far this can be achieved against the backdrop of radically changing technology and public attitudes towards surveillance. This is an updated version of a 2013 report paper on the same subject, State of the Art. Since 2013, there have been significant changes in social media, how it is used by terrorist groups, and the methods being developed to make sense of it.  The paper is structured as follows: Part 1 is an overview of social media use, focused on how it is used by groups of interest to those involved in counter-terrorism. This includes new sections on trends of social media platforms; and a new section on Islamic State (IS). Part 2 provides an introduction to the key approaches of social media intelligence (henceforth ‘SOCMINT’) for counter-terrorism. Part 3 sets out a series of SOCMINT techniques. For each technique a series of capabilities and insights are considered, the validity and reliability of the method is considered, and how they might be applied to counter-terrorism work explored. Part 4 outlines a number of important legal, ethical and practical considerations when undertaking SOCMINT work

Educational ecosystems for Information Science: the case of the University of Pisa

Interdisciplinarity is becoming increasingly important in education. With the rapidly evolving job market, an interdisciplinary education can prepare students for the flexibility and broad knowledge base required to adapt. At the University of Pisa, we recognized the value of an interdisciplinary educational environment during our participation in the European project EINFOSE, where we harmonized the entry requirements for master programs in Information Science. Prior to this project, we had been building study programs in Digital Humanities and Data Science, whose intersection organically nurtured a diverse learning space. Through this lens, we will reflect on the obstacles constituted by disciplinary barriers and stress the importance of a flexible and open ‘ecosystem’ for education. These conclusions will be supported by data analysis on the careers of our students over the last eight years

Automatic information search for countering covid-19 misinformation through semantic similarity

Trabajo Fin de Máster en Bioinformática y Biología ComputacionalInformation quality in social media is an increasingly important issue and misinformation problem has become even more critical in the current COVID-19 pandemic, leading people exposed to false and potentially harmful claims and rumours. Civil society organizations, such as the World Health Organization, have demanded a global call for action to promote access to health information and mitigate harm from health misinformation. Consequently, this project pursues countering the spread of COVID-19 infodemic and its potential health hazards. In this work, we give an overall view of models and methods that have been employed in the NLP field from its foundations to the latest state-of-the-art approaches. Focusing on deep learning methods, we propose applying multilingual Transformer models based on siamese networks, also called bi-encoders, combined with ensemble and PCA dimensionality reduction techniques. The goal is to counter COVID-19 misinformation by analyzing the semantic similarity between a claim and tweets from a collection gathered from official fact-checkers verified by the International Fact-Checking Network of the Poynter Institute. It is factual that the number of Internet users increases every year and the language spoken determines access to information online. For this reason, we give a special effort in the application of multilingual models to tackle misinformation across the globe. Regarding semantic similarity, we firstly evaluate these multilingual ensemble models and improve the result in the STS-Benchmark compared to monolingual and single models. Secondly, we enhance the interpretability of the models’ performance through the SentEval toolkit. Lastly, we compare these models’ performance against biomedical models in TREC-COVID task round 1 using the BM25 Okapi ranking method as the baseline. Moreover, we are interested in understanding the ins and outs of misinformation. For that purpose, we extend interpretability using machine learning and deep learning approaches for sentiment analysis and topic modelling. Finally, we developed a dashboard to ease visualization of the results. In our view, the results obtained in this project constitute an excellent initial step toward incorporating multilingualism and will assist researchers and people in countering COVID-19 misinformation