scholarly journals A context-aware notification framework for developers of computer supported collaborative environments

2005 ◽  
Author(s):  
◽  
Christopher J. Amelung
Keyword(s):  
Social Context ◽  
Sense Of Community ◽  
Social Contexts ◽  
User Preferences ◽  
User Preference ◽  
Context Aware ◽  
Collaborative Environments ◽  
Notification System ◽  
Development Framework ◽  
New Development

Researchers have identified user presence, awareness, and a sense of community as important components of Computer Supported Collaborative Environments (CSCE) (Dourish and Bellotti, 1992; Erickson and Kellogg, 2003; Moody, 2000; Prinz, 1999). To support user actions and interactions sufficient to create and sustain a sense of community, recent CSCE have been developed with notification systems to provide activity notifications to users. However, these notification systems typically transmit generic notifications as actions occur and do not provide mechanisms for analyzing and providing notifications based on user preference or social context. A challenge facing developers of CSCE is to create a notification system for delivering awareness information based on the ever-changing preferences, interests, and social contexts of users. To address this challenge, this study articulated and advanced a theoretical framework for developers to use when integrating activity notifications into existing CSCE. The proposed framework is based on the importance of user preferences and social context and is derived from the Locales Framework (Fitzpatrick, 1998). The principles of this new development framework are Social Context, Awareness in Context, Activity Discovery, Trends in Activity, Meaning of Activity, and Notification Customization. To evaluate the concepts of this framework, this study developed a context-aware activity notification system for an existing CSCE based on the framework's proposed principles. During the development process, it was determined that not only could the Framework for Notification be used to provide notifications based on user preference and social context, but the use of the proposed Framework afforded a richer understanding of the collaborative needs of users for both the theorists discussing the implications of activity notifications and the developers working to provide those notifications.

Social Context-aware Person Search in Videos via Multi-modal Cues

2022 ◽  
Vol 40 (3) ◽  
pp. 1-25
Author(s):  
Dan Li ◽  
Tong Xu ◽  
Peilun Zhou ◽  
Weidong He ◽  
Yanbin Hao ◽  
...  
Keyword(s):  
Social Context ◽  
Visual Cues ◽  
Search Task ◽  
Social Relation ◽  
Social Contexts ◽  
Social Cues ◽  
Context Aware ◽  
Semantic Cues ◽  
Person Search ◽  
High Level

Person search has long been treated as a crucial and challenging task to support deeper insight in personalized summarization and personality discovery. Traditional methods, e.g., person re-identification and face recognition techniques, which profile video characters based on visual information, are often limited by relatively fixed poses or small variation of viewpoints and suffer from more realistic scenes with high motion complexity (e.g., movies). At the same time, long videos such as movies often have logical story lines and are composed of continuously developmental plots. In this situation, different persons usually meet on a specific occasion, in which informative social cues are performed. We notice that these social cues could semantically profile their personality and benefit person search task in two aspects. First, persons with certain relationships usually co-occur in short intervals; in case one of them is easier to be identified, the social relation cues extracted from their co-occurrences could further benefit the identification for the harder ones. Second, social relations could reveal the association between certain scenes and characters (e.g., classmate relationship may only exist among students), which could narrow down candidates into certain persons with a specific relationship. In this way, high-level social relation cues could improve the effectiveness of person search. Along this line, in this article, we propose a social context-aware framework, which fuses visual and social contexts to profile persons in more semantic perspectives and better deal with person search task in complex scenarios. Specifically, we first segment videos into several independent scene units and abstract out social contexts within these scene units. Then, we construct inner-personal links through a graph formulation operation for each scene unit, in which both visual cues and relation cues are considered. Finally, we perform a relation-aware label propagation to identify characters’ occurrences, combining low-level semantic cues (i.e., visual cues) and high-level semantic cues (i.e., relation cues) to further enhance the accuracy. Experiments on real-world datasets validate that our solution outperforms several competitive baselines.

scholarly journals Individual behavioural traits not social context affects learning about novel objects in archerfish

2021 ◽  
Vol 75 (3) ◽  
Author(s):  
Nick A. R. Jones ◽  
Helen C. Spence-Jones ◽  
Mike Webster ◽  
Luke Rendell
Keyword(s):  
Social Context ◽  
Social Environment ◽  
Social Contexts ◽  
Negative Effects ◽  
Behavioural Phenotype ◽  
Social Species ◽  
The Social ◽  
Social Animals ◽  
Novel Objects ◽  
The Individual

Abstract Learning can enable rapid behavioural responses to changing conditions but can depend on the social context and behavioural phenotype of the individual. Learning rates have been linked to consistent individual differences in behavioural traits, especially in situations which require engaging with novelty, but the social environment can also play an important role. The presence of others can modulate the effects of individual behavioural traits and afford access to social information that can reduce the need for ‘risky’ asocial learning. Most studies of social effects on learning are focused on more social species; however, such factors can be important even for less-social animals, including non-grouping or facultatively social species which may still derive benefit from social conditions. Using archerfish, Toxotes chatareus, which exhibit high levels of intra-specific competition and do not show a strong preference for grouping, we explored the effect of social contexts on learning. Individually housed fish were assayed in an ‘open-field’ test and then trained to criterion in a task where fish learnt to shoot a novel cue for a food reward—with a conspecific neighbour visible either during training, outside of training or never (full, partial or no visible presence). Time to learn to shoot the novel cue differed across individuals but not across social context. This suggests that social context does not have a strong effect on learning in this non-obligatory social species; instead, it further highlights the importance that inter-individual variation in behavioural traits can have on learning. Significance statement Some individuals learn faster than others. Many factors can affect an animal’s learning rate—for example, its behavioural phenotype may make it more or less likely to engage with novel objects. The social environment can play a big role too—affecting learning directly and modifying the effects of an individual’s traits. Effects of social context on learning mostly come from highly social species, but recent research has focused on less-social animals. Archerfish display high intra-specific competition, and our study suggests that social context has no strong effect on their learning to shoot novel objects for rewards. Our results may have some relevance for social enrichment and welfare of this increasingly studied species, suggesting there are no negative effects of short- to medium-term isolation of this species—at least with regards to behavioural performance and learning tasks.

scholarly journals Predicting Implicit User Preferences with Multimodal Feature Fusion for Similar User Recommendation in Social Media

2021 ◽  
Vol 11 (3) ◽  
pp. 1064
Author(s):  
Jenq-Haur Wang ◽  
Yen-Tsang Wu ◽  
Long Wang
Keyword(s):  
Social Media ◽  
Feature Fusion ◽  
Relevant Information ◽  
Image Features ◽  
User Preferences ◽  
User Preference ◽  
Late Fusion ◽  
Multimodal Features ◽  
Fusion Methods ◽  
Text Features

In social networks, users can easily share information and express their opinions. Given the huge amount of data posted by many users, it is difficult to search for relevant information. In addition to individual posts, it would be useful if we can recommend groups of people with similar interests. Past studies on user preference learning focused on single-modal features such as review contents or demographic information of users. However, such information is usually not easy to obtain in most social media without explicit user feedback. In this paper, we propose a multimodal feature fusion approach to implicit user preference prediction which combines text and image features from user posts for recommending similar users in social media. First, we use the convolutional neural network (CNN) and TextCNN models to extract image and text features, respectively. Then, these features are combined using early and late fusion methods as a representation of user preferences. Lastly, a list of users with the most similar preferences are recommended. The experimental results on real-world Instagram data show that the best performance can be achieved when we apply late fusion of individual classification results for images and texts, with the best average top-k accuracy of 0.491. This validates the effectiveness of utilizing deep learning methods for fusing multimodal features to represent social user preferences. Further investigation is needed to verify the performance in different types of social media.

Time-aware cloud manufacturing service selection using unknown QoS prediction and uncertain user preferences

2021 ◽  
pp. 1063293X2110195
Author(s):  
Ying Yu ◽  
Shan Li ◽  
Jing Ma
Keyword(s):  
Time Series Prediction ◽  
Service Selection ◽  
Cloud Manufacturing ◽  
Service Evaluation ◽  
User Preferences ◽  
User Preference ◽  
Selection Methods ◽  
Qos Prediction ◽  
Qos Performance ◽  
Time Aware

Selecting the most efficient from several functionally equivalent services remains an ongoing challenge. Most manufacturing service selection methods regard static quality of service (QoS) as a major competitiveness factor. However, adaptations are difficult to achieve when variable network environment has significant impact on QoS performance stabilization in complex task processes. Therefore, dynamic temporal QoS values rather than fixed values are gaining ground for service evaluation. User preferences play an important role when service demanders select personalized services, and this aspect has been poorly investigated for temporal QoS-aware cloud manufacturing (CMfg) service selection methods. Furthermore, it is impractical to acquire all temporal QoS values, which affects evaluation validity. Therefore, this paper proposes a time-aware CMfg service selection approach to address these issues. The proposed approach first develops an unknown-QoS prediction model by utilizing similarity features from temporal QoS values. The model considers QoS attributes and service candidates integrally, helping to predict multidimensional QoS values accurately and easily. Overall QoS is then evaluated using a proposed temporal QoS measuring algorithm which can self-adapt to user preferences. Specifically, we employ the temporal QoS conflict feature to overcome one-sided user preferences, which has been largely overlooked previously. Experimental results confirmed that the proposed approach outperformed classical time series prediction methods, and can also find better service by reducing user preference misjudgments.

Mastery Of Sociolinguistic Concepts Of Pragmatic Skills By Junior High School Students

2021 ◽  
Vol 1 (1) ◽  
pp. 18-26
Author(s):  
Yossi Pratiwi ◽  
Sridelli Dakhi
Keyword(s):  
High School ◽  
High School Students ◽  
Social Context ◽  
Junior High School ◽  
Social Contexts ◽  
Junior High School Students ◽  
Pragmatic Language ◽  
School Students ◽  
Research Hypothesis ◽  
Pragmatic Skills

Abstract.  Skilled in pragmatic language, means skilled in using language forms ( words, phrases and clauses appropriately according to the conditions, situations and social contexts behind it. Such pragmatic skills may be established if the situation, conditions and social context behind the use of the language can be adequately mastered. This study aims to describe the percentage of contributions to the mastery of sociolinguistic concepts with pragmatic skills. In line with the purpose of the study, sociolinguistic mastery data with pragmatic skills of 28 sample people netted with test instruments and analyzed with statistics r¬2.From the results of the analysis conducted, obtained a determination index of 0.78 which means; mastery of sociolinguistic concepts contributes 78% to the achievement of students' pragmatic skills. In accordance with the results of the above analysis, it can be concluded that mastery of sociolinguistic concepts is a variable of criteria that contributes very meaningfully to the improvement of pragmatic skills. Thus, the research hypothesis yaang said that the mastery of the concept of sociolinguistics contributes meaningfully to the development of pragmatic skills of students of SMP Negeri 1 Nias Selatan, the truth is proven

scholarly journals Negotiating ‘Normal’: The Management of Feminine Identities in Rural Britain

2007 ◽  
Vol 12 (1) ◽  
pp. 169-180 ◽  
Author(s):  
Fiona Gill
Keyword(s):  
Social Context ◽  
Group Dynamics ◽  
Gender Norms ◽  
Coping Mechanisms ◽  
Social Contexts ◽  
Social Consequences ◽  
Identity Performance ◽  
Team Identity ◽  
Team Members ◽  
Private Lives

This paper examines the management of feminine identities in a women's rugby team in a rural British community. In so doing, the issue of new, and potentially problematic, forms of femininity are explored, with their attendant social consequences. The team, known as the Jesters, is situated in a social context which is dominantly masculine and heterosexist, with rigidly enforced gender roles. Due to their participation in rugby, a ‘man's game’, the Jesters are threatened with marginalisation for their apparent failure to conform to, and potential disruption of, established gender norms. This threat is managed through the performance of certain ‘inauthentic’ feminine identities (hyper-femininity and heterosexuality) on the part of the entire team. It is this ‘team identity’ which lies at the heart of this paper. This paper therefore examines the group dynamics of identity performance and negotiation. In negotiating ‘normal’ the Jesters are forced to confront changing gender norms and social contexts within the team itself. This paper also examines the difficulties faced by individuals when their own interests are opposed to the interests of the group of which they are a part. Although largely uncaring about the private lives of team members, the heterosexual members of the Jesters refuse to tolerate the performance of alternative versions of femininity when it may result in the exclusion of the team as a whole. This paper therefore examines the differing interests of heterosexual and lesbian femininities within a potentially marginalised group and some of the coping mechanisms adopted by both groups to develop a coherent team image.

scholarly journals Evolutionary Social Poisson Factorizationfor Temporal Recommendation

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
ChunYan Yin ◽  
YongHeng Chen ◽  
Wanli Zuo
Keyword(s):  
Recommendation Systems ◽  
Predictive Performance ◽  
User Preferences ◽  
Social Model ◽  
User Preference ◽  
Latent Factors ◽  
Factorization Model ◽  
Real World Datasets ◽  
Item Attributes ◽  
The Impact

AbstractPreference-based recommendation systems analyze user-item interactions to reveal latent factors that explain our latent preferences for items and form personalized recommendations based on the behavior of others with similar tastes. Most of the works in the recommendation systems literature have been developed under the assumption that user preference is a static pattern, although user preferences and item attributes may be changed through time. To achieve this goal, we develop an Evolutionary Social Poisson Factorization (EPF$$\_$$ _ Social) model, a new Bayesian factorization model that can effectively model the smoothly drifting latent factors using Conjugate Gamma–Markov chains. Otherwise, EPF$$\_$$ _ Social can obtain the impact of friends on social network for user’ latent preferences. We studied our models with two large real-world datasets, and demonstrated that our model gives better predictive performance than state-of-the-art static factorization models.

scholarly journals MILLENIUM DEVELOMPENT GOALS (MDGS) DAN SUSTAINABLE DEVELOPMENT GOALS (SDGS) DALAM KESEJAHTERAAN SOSIAL

BISMA ◽  
2018 ◽  
Vol 11 (3) ◽  
pp. 390
Author(s):  
Wahyuningsih Wahyuningsih
Keyword(s):  
Sustainable Development ◽  
Millennium Development Goals ◽  
Sustainable Development Goals ◽  
Social Protection ◽  
Action Plan ◽  
Global Challenge ◽  
Development Framework ◽  
The People ◽  
New Development ◽  
Development Goals

Abstract: Sustainable Development Goals (SDGs) are designed as the successor of the Millennium Development Goals (MDGs) as the MDGs’ goals have not been achieved by the end of 2015. The SDGs is an action plan for the humankind, the planet, and the prosperity that also aims to strengthen universal peace in a broad freedom. It exists to overcome extreme poverty as the greatest global challenge. The SDGs concept is needed as a new development framework that accommodates all the changes occur after the 2015-MDGs, especially related to the world's changes since 2000 regarding the issue of deflation of natural resources, environmental degradation, crucial climate change, social protection, food and energy security, and a more pro-poor development. MDGs aimed only for the developing countries, while SDGs have a more universal goal. The SDGs is present to replace the MDGs with better goals to face the world future challenge. It has 17 goals and 169 targets that will stimulate actions for the next 15 years, focusing on the significant areas for the humanity and the planet, i.e., the people, planet, prosperity, peace, and partnership. Keywords:     MDGs, SDGs, Social Welfare, Development.

Using Notification Systems to Create Social Places for Online Learning

2011 ◽  
pp. 1040-1050
Author(s):  
James M. Laffey ◽  
Christopher J. Amelung
Keyword(s):  
Online Learning ◽  
Context Awareness ◽  
Contextual Information ◽  
Learning Activity ◽  
Course Management Systems ◽  
Context Aware ◽  
Learning Context ◽  
Notification System ◽  
The Social ◽  
Critical Components

Context-aware activity notification systems have potential to improve and support the social experience of online learning. The authors of this chapter have developed a Context-aware Activity Notification System (CANS) that monitors online learning activities and represents relevant contextual information by providing notification and making the learning activity salient to other participants. The chapter describes previous efforts to develop and support online learning context awareness systems; it also defines the critical components and features of such a system. It is argued that notification systems can provide methods for using the context of activity to support members’ understanding of the meaning of activity. When designed and implemented effectively, CANS can turn course management systems (CMS) into technologies of social interaction to support the social requirements of learning.

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