Search (258 results, page 1 of 13)

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Abstract

In this research, we propose 3 different approaches to measure the semantic relatedness between 2 words: (i) boost the performance of GloVe word embedding model via removing or transforming abnormal dimensions; (ii) linearly combine the information extracted from WordNet and word embeddings; and (iii) utilize word embedding and 12 linguistic information extracted from WordNet as features for Support Vector Regression. We conducted our experiments on 8 benchmark data sets, and computed Spearman correlations between the outputs of our methods and the ground truth. We report our results together with 3 state-of-the-art approaches. The experimental results show that our method can outperform state-of-the-art approaches in all the selected English benchmark data sets.

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Abstract

In the blooming area of Internet technology, the concept of Internet-of-Things (IoT) holds a distinct position that interconnects a large number of smart objects. In the context of social IoT (SIoT), the argument of trust and reliability is evaluated in the presented work. The proposed framework is divided into two blocks, namely Verification Block (VB) and Evaluation Block (EB). VB defines various ontology-based relationships computed for the objects that reflect the security and trustworthiness of an accessed service. While, EB is used for the feedback analysis and proves to be a valuable step that computes and governs the success rate of the service. Support vector machine (SVM) is applied to categorise the trust-based evaluation. The security aspect of the proposed approach is comparatively evaluated for DDoS and malware attacks in terms of success rate, trustworthiness and execution time. The proposed secure ontology-based framework provides better performance compared with existing architectures.

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Abstract

To effectively manage a crisis, most decisions made by governments, organizations, communities, and individuals are based on "shared situational awareness" (SSA) derived from multiple information sources. Developing SSA depends on the alignment of mental models, which "represent our shared version of truth and reality on which we can act." Social media has facilitated public sensemaking during a crisis; however, it has also encouraged mental model dissonance, resulting in the digital destruction of mental models and undermining adequate SSA. The study is concerned with the challenges of creating SSA during the COVID-19 pandemic in Australia. This paper documents a netnography of Australian public health agencies' Facebook communication, exploring the initial impact of COVID-19 on SSA creation. Chaos theory is used as a theoretical lens to examine information perception, meaning, and assumptions relating to SSA from pre to post-pandemic periods. Our study highlights how the initial COVID-19 "butterfly effect" swamped the public health communication channel, leaving little space for other important health issues. This research contributes to information systems, information science, and communications by illustrating how the emergence of a crisis impacts social media communication, the creation of SSA, and what this means for social media adoption for crisis communication purposes.

Date

22. 9.2023 16:02:26

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Abstract

Purpose This article examines the relation between place, space and information behaviour. Design/methodology/approach Concepts of place and space are explored through a comparison of three leisure pursuits: running, urban exploration and genealogy, based on the authors' research and the published literature. Findings A socially constructed meaning of place is central to each leisure activity but how it is experienced physically, emotionally and imaginatively are different. Places have very different meanings within each practice. Mirroring this, information behaviours are also very different: such as the sources used, the type of information created and how it is shared or not shared. Information behaviour contributes to the meanings associated with place in particular social practices. Research limitations/implications Meaning attached to place can be understood as actively constructed within social practices. Rather than context for information behaviours in the sense of an outside, containing, even constraining, environment, the meaning of place can be seen as actively constructed within social practices and by the information behaviours that are part of them. Originality/value The paper adds a new perspective to the understanding of place and space in the study of information behaviour.

Date

5. 6.2022 17:20:22

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Abstract

To determine the author of a text's gender, various feature types have been suggested (e.g., function words, n-gram of letters, etc.) leading to a huge number of stylistic markers. To determine the target category, different machine learning models have been suggested (e.g., logistic regression, decision tree, k nearest-neighbors, support vector machine, naïve Bayes, neural networks, and random forest). In this study, our first objective is to know whether or not the same model always proposes the best effectiveness when considering similar corpora under the same conditions. Thus, based on 7 CLEF-PAN collections, this study analyzes the effectiveness of 10 different classifiers. Our second aim is to propose a 2-stage feature selection to reduce the feature size to a few hundred terms without any significant change in the performance level compared to approaches using all the attributes (increase of around 5% after applying the proposed feature selection). Based on our experiments, neural network or random forest tend, on average, to produce the highest effectiveness. Moreover, empirical evidence indicates that reducing the feature set size to around 300 without penalizing the effectiveness is possible. Finally, based on such reduced feature sizes, an analysis reveals some of the specific terms that clearly discriminate between the 2 genders.

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Abstract

This paper contains a report of two interdependent knowledge organization (KO) projects for an LGBT2QIA+ library. The authors, in the context of volunteer library work for an independent library, redesigned the classification system and subject cataloguing guidelines to centre LGBT2QIA+ subjects. We discuss the priorities of creating and maintaining knowledge organization systems for a historically marginalized community and address the challenge that queer subjectivity poses to the goals of KO. The classification system features a focus on identity and physically reorganizes the library space in a way that accounts for the multiple and overlapping labels that constitute the currently articulated boundaries of this community. The subject heading system focuses on making visible topics and elements of identity made invisible by universal systems and by the newly implemented classification system. We discuss how this project may inform KO for other marginalized subjects, particularly through process and documentation that prioritizes transparency and the acceptance of an unfinished endpoint for queer KO.

Date

6.10.2020 21:22:33

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Abstract

Increasingly we live through our personal screens; we work, play, socialize, and learn digitally. The shift to remote everything during the pandemic was another step in a decades-long march toward the digitization of everyday life made possible by innovations in media, information, and communication technology. In The Digital Environment, Pablo Boczkowski and Eugenia Mitchelstein offer a new way to understand the role of the digital in our daily lives, calling on us to turn our attention from our discrete devices and apps to the array of artifacts and practices that make up the digital environment that envelops every aspect of our social experience. Boczkowski and Mitchelstein explore a series of issues raised by the digital takeover of everyday life, drawing on interviews with a variety of experts. They show how existing inequities of gender, race, ethnicity, education, and class are baked into the design and deployment of technology, and describe emancipatory practices that counter this--including the use of Twitter as a platform for activism through such hashtags as #BlackLivesMatter and #MeToo. They discuss the digitization of parenting, schooling, and dating--noting, among other things, that today we can both begin and end relationships online. They describe how digital media shape our consumption of sports, entertainment, and news, and consider the dynamics of political campaigns, disinformation, and social activism. Finally, they report on developments in three areas that will be key to our digital future: data science, virtual reality, and space exploration.

Content

1. Three Environments, One Life -- Part I: Foundations -- 2. Mediatization -- 3. Algorithms -- 4. Race and Ethnicity -- 5. Gender -- Part II: Institutions -- 6. Parenting -- 7. Schooling -- 8. Working -- 9. Dating -- Part III: Leisure -- 10. Sports -- 11. Televised Entertainment -- 12. News -- Part IV: Politics -- 13. Misinformation and Disinformation -- 14. Electoral Campaigns -- 15. Activism -- Part V: Innovations -- 16. Data Science -- 17. Virtual Reality -- 18. Space Exploration -- 19. Bricks and Cracks in the Digital Environment

Date

22. 6.2023 18:25:18

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Abstract

Surveillance, as a concept and social practice, is inextricably linked to information. It is, at its core, about information extraction and analysis conducted for some regulatory purpose. Yet, information science research only sporadically leverages surveillance studies scholarship, and we see a lack of sustained and focused attention to surveillance as an object of research within the domains of information behavior and social informatics. Surveillance, as a range of contextual and culturally based social practices defined by their connections to information seeking and use, should be framed as information practice-as that term is used within information behavior scholarship. Similarly, manifestations of surveillance in society are frequently perfect examples of information and communications technologies situated within everyday social and organizational structures-the very focus of social informatics research. The technological infrastructures and material artifacts of surveillance practice-surveillance technologies-can also be viewed as information tools. Framing surveillance as information practice and conceptualizing surveillance technologies as socially and contextually situated information tools can provide space for new avenues of research within the information sciences, especially within information disciplines that focus their attention on the social aspects of information and information technologies in society.

Date

22. 3.2023 11:57:47

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Abstract

Logical rules are essential for uncovering the logical connections between relations, which could improve the reasoning performance and provide interpretable results on knowledge graphs (KGs). Although there have been many efforts to mine meaningful logical rules over KGs, existing methods suffer from the computationally intensive searches over the rule space and a lack of scalability for large-scale KGs. Besides, they often ignore the semantics of relations which is crucial for uncovering logical connections. Recently, large language models (LLMs) have shown impressive performance in the field of natural language processing and various applications, owing to their emergent ability and generalizability. In this paper, we propose a novel framework, ChatRule, unleashing the power of large language models for mining logical rules over knowledge graphs. Specifically, the framework is initiated with an LLM-based rule generator, leveraging both the semantic and structural information of KGs to prompt LLMs to generate logical rules. To refine the generated rules, a rule ranking module estimates the rule quality by incorporating facts from existing KGs. Last, a rule validator harnesses the reasoning ability of LLMs to validate the logical correctness of ranked rules through chain-of-thought reasoning. ChatRule is evaluated on four large-scale KGs, w.r.t. different rule quality metrics and downstream tasks, showing the effectiveness and scalability of our method.

Date

23.11.2023 19:07:22

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Abstract

It is well known that, within the Latin production of written text, peculiar metric schemes were followed not only in poetic compositions, but also in many prose works. Such metric patterns were based on so-called syllabic quantity, that is, on the length of the involved syllables, and there is substantial evidence suggesting that certain authors had a preference for certain metric patterns over others. In this research we investigate the possibility to employ syllabic quantity as a base for deriving rhythmic features for the task of computational authorship attribution of Latin prose texts. We test the impact of these features on the authorship attribution task when combined with other topic-agnostic features. Our experiments, carried out on three different datasets using support vector machines (SVMs) show that rhythmic features based on syllabic quantity are beneficial in discriminating among Latin prose authors.

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Abstract

To support historians in their work, we need to understand their work-related needs and propose what is required to support those needs. Although the quantity of digitized historical documents available is increasing, historians' ways of working with the digital documents have not been widely studied, particularly in authentic work settings. To better support the historians' reasoning processes, we investigate history researchers' work tasks as the context of information interaction and examine their cognitive access points into information. The analysis is based on a longitudinal observational research and interviews in a task-based research setting. Based on these findings in the historians' cognitive space, we build bridges into the document space. By studying the information interactions in real task contexts, we facilitate the provision of task-specific handles into documents that can be used in designing digital research tools for historians.

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Abstract

Diachronic word embeddings-vector representations of words over time-offer remarkable insights into the evolution of language and provide a tool for quantifying sociocultural change from text documents. Prior work has used such embeddings to identify shifts in the meaning of individual words. However, simply knowing that a word has changed in meaning is insufficient to identify the instances of word usage that convey the historical meaning or the newer meaning. In this study, we link diachronic word embeddings to documents, by situating those documents as leaders or laggards with respect to ongoing semantic changes. Specifically, we propose a novel method to quantify the degree of semantic progressiveness in each word usage, and then show how these usages can be aggregated to obtain scores for each document. We analyze two large collections of documents, representing legal opinions and scientific articles. Documents that are scored as semantically progressive receive a larger number of citations, indicating that they are especially influential. Our work thus provides a new technique for identifying lexical semantic leaders and demonstrates a new link between progressive use of language and influence in a citation network.

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Abstract

Inferring the gender of named entities present in a text has several practical applications in information sciences. Existing approaches toward name gender identification rely exclusively on using the gender distributions from labeled data. In the absence of such labeled data, these methods fail. In this article, we propose a two-stage model that is able to infer the gender of names present in text without requiring explicit name-gender labels. We use coreference resolution as the backbone for our proposed model. To aid coreference resolution where the existing contextual information does not suffice, we use a retrieval-assisted context aggregation framework. We demonstrate that state-of-the-art name gender inference is possible without supervision. Our proposed method matches or outperforms several supervised approaches and commercially used methods on five English language datasets from different domains.

Date

22. 3.2023 12:00:14

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Abstract

Purpose This paper offers a definition of the core of information science, which encompasses most research in the field. The definition provides a unique identity for information science and positions it in the disciplinary universe. Design/methodology/approach After motivating the objective, a definition of the core and an explanation of its key aspects are provided. The definition is related to other definitions of information science before controversial discourse aspects are briefly addressed: discipline vs. field, science vs. humanities, library vs. information science and application vs. theory. Interdisciplinarity as an often-assumed foundation of information science is challenged. Findings Information science is concerned with how information is manifested across space and time. Information is manifested to facilitate and support the representation, access, documentation and preservation of ideas, activities, or practices, and to enable different types of interactions. Research and professional practice encompass the infrastructures - institutions and technology -and phenomena and practices around manifested information across space and time as its core contribution to the scholarly landscape. Information science collaborates with other disciplines to work on complex information problems that need multi- and interdisciplinary approaches to address them. Originality/value The paper argues that new information problems may change the core of the field, but throughout its existence, the discipline has remained quite stable in its central focus, yet proved to be highly adaptive to the tremendous changes in the forms, practices, institutions and technologies around and for manifested information.

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Abstract

This article outlines the early process and reflects on the experiences of the authors as members of a team creating a Hawaiian knowledge organization system. The authors put forward shared understanding as a process, not a goal, and a way to reimagine and elucidate the process of knowledge organization work. As the project has progressed, team members have embraced their work as not solely knowledge creation and organization, but also communication. The group has identified a metaphorical frame, community agreements, knowledge graphs, and authority record templates as communication tools that are critical to creating a shared space to discuss meaning.

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Abstract

In a digital library, book search is one of the most important information services. However, with the rapid development of network technologies such as cloud computing, the server-side of a digital library is becoming more and more untrusted; thus, how to prevent the disclosure of users' book query privacy is causing people's increasingly extensive concern. In this article, we propose to construct a group of plausible fake queries for each user book query to cover up the sensitive subjects behind users' queries. First, we propose a basic framework for the privacy protection in book search, which requires no change to the book search algorithm running on the server-side, and no compromise to the accuracy of book search. Second, we present a privacy protection model for book search to formulate the constraints that ideal fake queries should satisfy, that is, (i) the feature similarity, which measures the confusion effect of fake queries on users' queries, and (ii) the privacy exposure, which measures the cover-up effect of fake queries on users' sensitive subjects. Third, we discuss the algorithm implementation for the privacy model. Finally, the effectiveness of our approach is demonstrated by theoretical analysis and experimental evaluation.

Date

6. 1.2020 17:22:25

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Abstract

Purpose The purpose of this paper is to propose a theoretical framework to illustrate the archival knowledge applied by archivists in their personal archiving (PA) and the mechanism of the application of archival knowledge in their PA. Design/methodology/approach The grounded theory methodology was adopted. For data collection, in-depth interviews were conducted with 21 archivists in China. Data analysis was performed using the open coding, axial coding and selective coding to organise the archival knowledge composition of PA and develops the awareness-knowledge-action (AKA) integration model of archival knowledge application in the field of PA, according to the principles of the grounded theory. Findings The archival knowledge involved in the field of PA comprises four principal categories: documentation, arrangement, preservation and appraisal. Three interactive factors involved in archivists' archival knowledge application in the field of PA behaviour: awareness, knowledge and action, which form a pattern of awareness leading, knowledge guidance and action innovation, and archivists' PA practice is flexible and innovative. The paper underscored that it is need to improve archival literacy among general public. Originality/value The study constructs a theoretical framework to identify the specialised archival knowledge and skills of PA which is able to provide solutions for non-specialist PA and develops an AKA model to explain the interaction relationships between awareness, knowledge and action in the field of PA.

Date

22. 1.2021 14:20:27

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Abstract

Drawing from social cognitive theory, the purpose of this study is to examine how personal, environmental and behavioral factors can interplay to influence people's use of YouTube as a learning resource. Design/methodology/approach This study proposed a conceptual model, which was then tested with data collected from a survey with 150 participants who had the experience of using YouTube for learning. The bootstrap method was employed to test the direct and mediation hypotheses in the model. Findings The results revealed that personal factors, i.e. learning outcome expectations and attitude, had direct effects on using YouTube as a learning resource (person ? behavior). The environmental factor, i.e. the sociability of YouTube, influenced the attitude (environment ? person), while the behavioral factor, i.e. prior experience of learning on YouTube, affected learning outcome expectations (behavior ? person). Moreover, the two personal factors fully mediated the influences of sociability and prior experience on YouTube usage for learning. Practical implications The factors and their relationships identified in this study provide important implications for individual learners, platform designers, educators and other stakeholders who encourage the use of YouTube as a learning resource. Originality/value This study draws on a comprehensive theoretical perspective (i.e. social cognitive theory) to investigate the interplay of critical components (i.e. individual, environment and behavior) in YouTube's learning ecosystem. Personal factors not only directly influenced the extent to which people use YouTube as a learning resource but also mediated the effects of environmental and behavioral factors on the usage behavior.

Date

20. 1.2015 18:30:22

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Abstract

In recent years, cross-modal retrieval has been a popular research topic in both fields of computer vision and natural language processing. There is a huge semantic gap between different modalities on account of heterogeneous properties. How to establish the correlation among different modality data faces enormous challenges. In this work, we propose a novel end-to-end framework named Dual Multi-Angle Self-Attention (DMASA) for cross-modal retrieval. Multiple self-attention mechanisms are applied to extract fine-grained features for both images and texts from different angles. We then integrate coarse-grained and fine-grained features into a multimodal embedding space, in which the similarity degrees between images and texts can be directly compared. Moreover, we propose a special multistage training strategy, in which the preceding stage can provide a good initial value for the succeeding stage and make our framework work better. Very promising experimental results over the state-of-the-art methods can be achieved on three benchmark datasets of Flickr8k, Flickr30k, and MSCOCO.

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Abstract

The emergence of large multi-institutional digital libraries has opened the door to aggregate-level examinations of the published word. Such large-scale analysis offers a new way to pursue traditional problems in the humanities and social sciences, using digital methods to ask routine questions of large corpora. However, inquiry into multiple centuries of books is constrained by the burdens of scale, where statistical inference is technically complex and limited by hurdles to access and flexibility. This work examines the role that exploratory data analysis and visualization tools may play in understanding large bibliographic datasets. We present one such tool, HathiTrust+Bookworm, which allows multifaceted exploration of the multimillion work HathiTrust Digital Library, and center it in the broader space of scholarly tools for exploratory data analysis.