Hidden Context Research Articles

Comparative learning based stance agreement detection framework for multi-target stance detection

Multi-target stance detection is the detection of the stance of multiple targets in text. Currently, most multi-target stance detection methods only detect the stance of two targets individually and do not make the two targets complement each other to take full advantage of the relevant semantic information between the two targets. In this paper, we propose a comparative learning based stance agreement detection framework. We applied contrastive learning to stance agreement detection, it enabled the model to learn more information about the features of the target and to strengthen the links between the semantic information of the targets so that they assist each other in stance detection. In addition, we fine-tuned a new model as our encoder to more fully exploit the semantic information between hidden contexts. We also apply joint training as a multi-task learning approach, allowing models to share domain-specific information based on the dataset. By comparing different methods, experimental results show that our method achieves state-of-the-art results on multi-target benchmark datasets. In the concluding sections of our paper, we conducted error analysis experiments on the proposed methodology, elucidating its inherent limitations and furnishing invaluable insights conducive to future enhancements.

Stonewall forever: queer monumentality in the age of augmented reality

ABSTRACT In this article, I examine Stonewall Forever, a mobile augmented reality (AR) application developed by Google and the U.S. National Parks Service, that superimposes computer-generated imagery into users’ lines of vision to shape public memories of the Stonewall National Monument. I argue the app functions rhetorically as a visual-material chronotope because it spatiotemporally reorients visions toward otherwise hidden contexts in which multiply marginalized people acted as primary agents in the events surrounding the Stonewall riots. However, even as the app renders visible the contributions of minoritized communities in a landmark moment in LGBTQ + history, it repackages the bodies of now deceased trans of color revolutionaries as icons within a homonationalist frame, obscuring the ongoing callousness of a nation-state that has yet to provide systemic protections for the very identities it memorializes. My criticism of the app focuses on how institutional powers may leverage emerging visual media to generate more inclusive historical storylines as a technique for both managing changing cultural expectations regarding representational diversity and to serve national interests, a nascent but nonetheless profound effect of the gradually coalescing domains of queer monumentality and official U.S. commemorative traditions.

Legal Imagination, the Power of Texts and some Hidden Contexts

Legal Imagination, the Power of Texts and some Hidden Contexts

Legal Imagination, the Power of Texts and some Hidden Contexts

Legal Imagination, the Power of Texts and some Hidden Contexts

TextSpamDetector: textual content based deep learning framework for social spam detection using conjoint attention mechanism

Online Social Networks (OSNs) allow easy membership leading to registration of a huge population and generation of voluminous information. These characteristics attract spammers to spread spam which may cause annoyance, financial loss, or personal information loss to the user and also weaken the reputation of social network sites. Most of the spam detection methods are based on user and content-based features using machine learning techniques. But, these annotated features are difficult to extract in real-time due to the privacy policy of most social network sites. Even for the features that can be extracted, because of their large size, the manual extraction process is complex and time-consuming. So there is a need for text level spam detection that does not require extraction of hard-core features. Existing deep learning based or existing single attention mechanism based text classification methods could not perform well as social network data are sparse with short texts and noises. Moreover, Spammers avoid direct spam words and use indirect words to evade spam filtering techniques and thus resulting in the dynamic and non-stationary nature of the social network spam texts. These indirect words contain hidden context that creates attention drift problem. So conjoint attention mechanism along with two attention mechanisms namely normal attention and context preserving attention are proposed to avoid attention drift problem in this deep learning-based text level spam detection technique (TextSpamDetector). Attention drift problem is solved by one attention mechanism which helps to find the important words while another attention mechanism allows focusing on attention in target context by referring to higher level abstraction of context vector. These attention mechanisms are referring to different context representations of the input text for finding informative words from the structural context representation. This structural context representation containing both local semantic features as well as global semantic dependency features is generated by CNN and BiLSTM. The proposed model is evaluated with the existing spam detection techniques using three datasets and the experimental results have proved that the proposed model performs well in terms of accuracy, F measure, and false-positive rate.

A multi-technique approach to contextualising painted rock art in the Central Pilbara of Western Australia: Integrating in-field and laboratory methods

For nearly 70 years scientific techniques have been routinely applied in archaeological research. Yet some artefacts hold such cultural significance that sampling is inappropriate, restricting the methods that can be brought to bear in their analysis. Such restrictions often apply to rock art, especially where research is directed by the indigenous peoples who have stewardship over not only the site fabric, but its inseparable cultural context. Here we report a multi-technique program of in-field and laboratory-based analyses to describe the materiality of a painted rock art site in Nyiyaparli country, in the Central Pilbara region of Western Australia. The relationship between the rock art, nearby potential pigment sources and evidence for ochre processing at the site was investigated using in situ portable X-Ray Fluorescence and optical microscopy, with interpretations aided by field and laboratory-based residue analysis of grinding related stone artefacts and X-Ray Powder Diffraction of potential ochre sources. Our findings provide an example of the nuanced interpretations that scientific analyses can add to rock art investigations. Our work suggests that local materials were used in the production of painted art and that ochre processing was ubiquitous at the site and other nearby rockshelters. Combined with the placement of rock art in a hidden context within the site, we suggest the panels at BBH15-01 were part of in-group events and that art and ochre processing in the Baby Hope study area were part of everyday activities.

Contextual bandits with hidden contexts: a focused data capture from social media streams

This paper addresses the problem of real time data capture from social media. Due to different limitations, it is not possible to collect all the data produced by social networks such as Twitter. Therefore, to be able to gather enough relevant information related to a predefined need, it is necessary to focus on a subset of the information sources. In this work, we focus on user-centered data capture and consider each account of a social network as a source that can be followed at each iteration of a data capture process. This process, whose aim is to maximize the cumulative utility of the captured information for the specified need, is constrained at each time step by the number of users that can be monitored simultaneously. The problem of selecting a subset of accounts to listen to over time is a sequential decision problem under constraints, which we formalize as a bandit problem with multiple selections. In this work, we propose a contextual UCB-like approach, that uses the activity of any user during the current step to predict his future behavior. Besides the capture of usefulness variations, considering contexts also enables to improve the efficiency of the process by leveraging some structure in the search space. However, existing contextual bandit approaches do not fit for our setting where most of the contexts are hidden from the agent. We therefore propose a new algorithm, called HiddenLinUCB, which aims at dealing with such missing information via variational inference. Experiments demonstrate the very good behavior of this approach compared to existing methods for tasks of data capture from social networks.

“Living in the brothel”: Participant observation in hidden contexts

This article describes the difficulties of the research and application of participant observation in hidden contexts and in behaviours that are considered taboo or intimate in western societies. Ethnographic work in four brothels of female prostitution was carried out in four Spanish cities, in which the author lived with the women and employees of the brothels. Aspects that arise during the ethnographic work are reflected upon: selection of and access to the spaces of interaction, the roles to be carried out by the researcher, the limits of the participation, the legal and ethical codes, acceptance by the informants and the learning of hidden meanings. Managing to pierce hidden contexts and meanings is only possible through participant observation with very close relationships of trust with the subjects under study, which is only attainable through daily coexistence.

THE IMPACT OF USING TECHNOLOGY-BASED COMMUNICATION ON THE QUALITY OF WORK RELATIONSHIPS

INTRODUCTION
 The use of modern technologies has changed the work setting and this change offers us many advantages and benefits. Technology based communication allows us to span time and distance among people. Technology development is moving at such speed that social human behaviour science has not kept pace. There is enormous research on human behaviour, but we lack new models for guiding managerial practices. The question is how to have highly performing, motivated and satisfied employees within companies, where communication is fully or partly technology based.
 MATERIALS AND METHODS
 The current article has described the relevant literature pointing out the most important theories and influencing aspects of the presented contextual model. The conceptual model, developed by the authors, shows that the relationship between a technology-based communication work setting and the quality of relationships is moderated by culture and the development of social relationships among employees.
 RESULTS
 From the presented literature review it can be concluded that technology-based communication (the amount of technology used) affects the quality of work relationships, which is mediated by culture and can be influenced by face-to-face events and norms. The more work communication is done through technology-based means, the harder it is to maintain high quality relationships inside the company.
 Communication via technology has a negative effect mainly because of misunderstandings and anonymity. Considering cultural differences and implementing suggestions for the development of social relationships, the quality of relationships can be improved.
 DISCUSSION
 First of all, the cultural differences have to be taken into account, especially in a multicultural context. Low Context culture members tend to be more specific and clear with their messages, while High Context culture members tend to have hidden context and messages that are not so clear, because of missing context that is rooted in the past.
 Another mediator that can improve the quality of relationships is development of social relationships.
 For further research the authors recognize the importance of leadership as the most important role in maintaining good quality relationships within the company.
 In future research this model should be continued by investigating the technology-based communications’ effect on work motivation and work satisfaction. The quality of work relationships are expected to have an influence on employee satisfaction and this idea could be discussed in order to extend the current model.
 CONCLUSION
 The connection of these variables is clear and the more that communication in the company is through technology-based means, the less is the quality of relationships among members. There are several suggestions for improving these relationships.
 In this article, the lack of concentration on human behaviour science in Computer Supported Cooperative Work is recognized. The future competitive advantage will be a motivated work force in combination with advanced technologies.

Konstruksi Feminisme Perempuan Sumba

In much feminist literatures show that women often have been underneath men power. This study aims to analyze about women representation in film “Marlina si Pembunuh dalam Empat Babak”. The method is critical discourse to see hidden contexts in this film with a gender perspective. Some scenes show that woman had a choice to protect herself. The main character of this film, Marlina tried to give a poison and murdered the thieves who want to robber and rape her. Those Marlina’s acts were different if we comparing with women stereotype that existed. Women were described as a second person, gentle and depend on men. The feminist movement in this film show women’s emancipation in social life, struggle to protect her body and family problems in Sumba’s woman.

隠蔽された : 『舞姫』を視座として( 日本文学協会第63回大会(第一日目) 文学教育の転回と希望- を掘り起こして-)

隠蔽された : 『舞姫』を視座として( 日本文学協会第63回大会(第一日目) 文学教育の転回と希望- を掘り起こして-)

Obituary

John E. Reilly (1928–2015), one of the founding members of the Poe Studies Association, Honorary PSA Member, and emeritus professor of English at the College of the Holy Cross, died on October 28, 2014, and is buried in Notre Dame Cemetery in Worcester, Massachusetts. A member of the American Antiquarian Society and on the editorial boards of Poe Studies/Dark Romanticism and the Edgar Allan Poe Review, Dr. Reilly was also a lector, a Eucharistic minister, a member of the Liturgy Committee, the choir, and the Parish Council in St. Charles Borromeo Parish in Worcester.Those who knew John remember him as an affable, kind, and generous man whose interest in Poe continued his whole life. We welcomed his participation at the bicentennial Poe conference in Philadelphia in 2009 where he chaired two panels: one on “Hidden Contexts” and the other on “Humor,” both interests of Dr. Reilly's. “The Lesser Death-Watch and ‘The Tell-Tale Heart’” published in one of the first issues of American Transcendental Quarterly deals quite literally with a hidden context and now appears at the Edgar Allan Poe Society of Baltimore's website, http://www.eapoe.org/papers/misc1921/jer19691.htm. We can also find Reilly's “Poe in American Drama: Versions of the Man,” http://www.eapoe.org/papers/psbbooks/pb19861d.htm, and “The Image of Poe in American Poetry,” http://www.eapoe.org/papers/psblctrs/pl19751.htm, there as well. For an intimate look at Dr. Reilly's academic career in his own words and a complete list of his works on Poe, see my 2000 “Interview with John Reilly” in the Edgar Allan Poe Review.

Finding Hidden Context: An Alternative Qualitative Approach for Social Welfare Research

Finding Hidden Context: An Alternative Qualitative Approach for Social Welfare Research

Hidden contexts and invisible power relations: A Foucauldian reading of diversity research

This article joins recent critical diversity studies that point to an urgent need to revitalize the field, but goes further by showing the inherent contextual issues and power relations that frame existing contributions. Based on a theoretical reading inspired by Michel Foucault, diversity is presented as discourse that is not independent of the particular research exercise of which it is part but, rather, remains contingent on the prevailing forms of knowledge and choices made by researchers. By attending to more refined understandings of power and context within diversity discourse, this article makes visible and calls into question the categorization and normalization of diversity and its management. It contributes to existing research by suggesting that the knowledge produced by mainstream and critical diversity scholars alike is biopolitical and governmental. To do diversity research differently or ‘otherwise’ requires finding ways to develop theorizations and practices that turn this modality of power against itself.

Survey on change detection over data stream

Data stream is a type of dynamic data,which is driven by some hidden contexts and may change with time.Generally speaking,the change implies some event in the real world.To detect change over data stream timely and accurately has a quite wide range of practical applications,and has been one of the hot topics in data stream mining.In this paper,a comprehensive survey on data stream change detection was presented,and the key task of change detection was introduced.An inductive unifying framework of change detection process was also given.Besides,a variety of already existing change detection approaches and their features were reviewed and evaluated in detail.Finally,the research outlook of data stream change detection was discussed.

Review of Matthews, Victor H., , More than Meets the Ear: Discovering the Hidden Contexts of Old Testament Conversations (Grand Rapids, Mich.: Eerdmans, 2008).

Review of Matthews, Victor H., , More than Meets the Ear: Discovering the Hidden Contexts of Old Testament Conversations (Grand Rapids, Mich.: Eerdmans, 2008).

Predictive Tabla Modelling Using Variable-length Markov and Hidden Markov Models

Tabla is a sophisticated, centuries-old percussion tradition from North India based on timbral sequences. We model these sequences in a predictive framework with Variable-length Markov Models (VLMMs). Using a database containing nearly 30,000 strokes in 35 compositions, we show that VLMMs have high predictive accuracy, with an average perplexity of 1.80, and median perplexity of 1.19, on a task with 42 distinct symbols. This basic framework is extended by the introduction of several new smoothing techniques that determine how to integrate predictions from the different order models. The model is then extended to include parallel representations of the sequence, a technique known as Multiple Viewpoint modelling. The work is then extended to the problem of recognizing strokes from audio. In this hidden context, the identity of the previous stroke is not revealed at each time step. A Variable-length Hidden Markov Model (VLHMM) is used to determine the next-symbol distribution that is used in computing the perplexity. We detail how the forward probabilities can be efficiently computed for the VLHMM by traversing a prediction suffix tree (PST) that is used to represent sequences. Using a VLHMM with a maximum order of 3, we obtain an average perplexity of 2.31, with a median of 1.16 on a nine-target task. To the best of our knowledge, this is the first use of Variable-length Hidden Markov Models for music modelling or prediction.

More than Meets the Ear: Discovering the Hidden Contexts of Old Testament Conversations – By Victor H. Matthews

More than Meets the Ear: Discovering the Hidden Contexts of Old Testament Conversations – By Victor H. Matthews

Review of Victor Matthew,More than Meets the Ear: Discovering the Hidden Contexts of Old Testament Conversations

Review of Victor Matthew,<i>More than Meets the Ear: Discovering the Hidden Contexts of Old Testament Conversations</i>

Adaptive Assembly

Adaptive Assembly is the name I have given to an integrative tool that I designed to harmonize participatory practices, creatively. This is needed because gaps in mutual understandings commonly emerge where collaborative teams include members from different disciplinary backgrounds and/or cognitive styles. Adaptive Assembly is a new approach to closing the gap between dispersed information and a task's participants. Here, co-authorship is also a cooperative act; therefore writing can be understood within the same terms of reference as design practice. For writers, Adaptive Assembly situates information in an ecological context by which to enable inter-relationships, and from which, newly dynamic information can emerge (e.g., subjects and hidden contexts). The benefit of this ecological method draws participants such as co-authors together to enable a focus and maps out paths towards its realization (e.g., chapters and their categories), each to be envisaged and implemented, incrementally.