Information Service Mashup for Industrial Knowledge Innovation Cluster under the Social Network Environment

2014 ◽  
Author(s):  
Weiwei Yan ◽  
Peng Cao
Keyword(s):  
Social Network ◽  
Information Service ◽  
Network Environment ◽  
Innovation Cluster ◽  
Knowledge Innovation ◽  
The Social

scholarly journals Challenges of Health Games in the Social Network Environment

2012 ◽  
Vol 1 (2) ◽  
pp. 171-173
Author(s):  
Hugo Paredes ◽  
Anabela Pinho ◽  
Nelson Zagalo
Keyword(s):  
Social Network ◽  
Network Environment ◽  
The Social

Interactive and Cognitive Models in the Social Network Environment for Designing

2012 ◽  
pp. 42-63
Author(s):  
Hung-Pin Hsu
Keyword(s):  
Social Network ◽  
Collaborative Design ◽  
Network Environment ◽  
Face To Face ◽  
Interactive Behavior ◽  
Depth Interview ◽  
The Social ◽  
Design Activities ◽  
New Type ◽  
Three Stages

In recent years, Metaverse has become a new type of social network. It provides an integrated platform and interactive environment for users to design artifacts and cooperate with each other. Facing this new type of social network, this chapter focuses on the cognitive and interactive behavior of users in the collaborative design activities. The chapter consists of three stages. In stage one the chapter introduces related theories and previous studies in order to present the Metaverse features. In stage two, the author chooses two different design and interactive environments to compare with Metaverse, which are, a normal face to face environment and a regular distance environment. Then the author executes three experiments in these different environments. In stage three, the author analyzes the retrospective data of three experiments with qualitative analysis by undertaking contextual inquiries in order to structure cognitive and interactive models of three environments. Furthermore, the author also executes an in-depth interview to get the qualitative data of subjects’ opinion. Finally, the affinity diagrams could be established with these models and the interview to provide knowledge of Metaverse for readers who research or develop social network environment.

Artificial intelligence against hate: Intervention reducing verbal aggression in the social network environment

2021 ◽  
Author(s):  
Michał Bilewicz ◽  
Patrycja Tempska ◽  
Gniewosz Leliwa ◽  
Maria Dowgiałło ◽  
Michalina Tańska ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Social Network ◽  
Verbal Aggression ◽  
Network Environment ◽  
The Social

The social network

2013 ◽  
Vol 44 (2) ◽  
pp. 22
Author(s):  
ALAN ROCKOFF
Keyword(s):  
Social Network ◽  
The Social

The Multilevel p2 Model

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 42-47 ◽  
Author(s):  
Bonne J. H. Zijlstra ◽  
Marijtje A. J. van Duijn ◽  
Tom A. B. Snijders
Keyword(s):  
Social Network ◽  
Network Data ◽  
Mcmc Algorithm ◽  
Independent Observation ◽  
Single Observation ◽  
Multiple Networks ◽  
Social Network Data ◽  
Multiple Observations ◽  
Practical Support ◽  
The Social

The p 2 model is a random effects model with covariates for the analysis of binary directed social network data coming from a single observation of a social network. Here, a multilevel variant of the p 2 model is proposed for the case of multiple observations of social networks, for example, in a sample of schools. The multilevel p 2 model defines an identical p 2 model for each independent observation of the social network, where parameters are allowed to vary across the multiple networks. The multilevel p 2 model is estimated with a Bayesian Markov Chain Monte Carlo (MCMC) algorithm that was implemented in free software for the statistical analysis of complete social network data, called StOCNET. The new model is illustrated with a study on the received practical support by Dutch high school pupils of different ethnic backgrounds.

ПРАГМАТИЧНИЙ ПОТЕНЦІАЛ НАТИВНОЇ РЕКЛАМИ: ФОРМИ, ТРЕНДИ (НА ПРИКЛАДІ НАТИВНОГО КОНТЕНТУ В СОЦІАЛЬНІЙ МЕРЕЖІ FACEBOOK ЩОДО БРЕНДА ФАКУЛЬТЕТУ ЖУРНАЛІСТИКИ ЗНУ)

2020 ◽  
pp. 113
Author(s):  
V. Kovpak ◽  
N. Trotsenko
Keyword(s):  
Social Network ◽  
Professional Training ◽  
Educational Process ◽  
Communication Strategy ◽  
Student Centered ◽  
Teacher Student ◽  
The Social ◽  
National University ◽  
High Level ◽  
The Impact

<div><p><em>The article analyzes the peculiarities of the format of native advertising in the media space, its pragmatic potential (in particular, on the example of native content in the social network Facebook by the brand of the journalism department of ZNU), highlights the types and trends of native advertising. The following research methods were used to achieve the purpose of intelligence: descriptive (content content, including various examples), comparative (content presentation options) and typological (types, trends of native advertising, in particular, cross-media as an opportunity to submit content in different formats (video, audio, photos, text, infographics, etc.)), content analysis method using Internet services (using Popsters service). And the native code for analytics was the page of the journalism department of Zaporizhzhya National University on the social network Facebook. After all, the brand of the journalism department of Zaporozhye National University in 2019 celebrates its 15th anniversary. The brand vector is its value component and professional training with balanced distribution of theoretical and practical blocks (seven practices), student-centered (democratic interaction and high-level teacher-student dialogue) and integration into Ukrainian and world educational process (participation in grant programs).</em></p></div><p><em>And advertising on social networks is also a kind of native content, which does not appear in special blocks, and is organically inscribed on one page or another and unobtrusively offers, just remembering the product as if «to the word». Popsters service functionality, which evaluates an account (or linked accounts of one person) for 35 parameters, but the main three areas: reach or influence, or how many users evaluate, comment on the recording; true reach – the number of people affected; network score – an assessment of the audience’s response to the impact, or how far the network information diverges (how many share information on this page).</em></p><p><strong><em>Key words:</em></strong><em> nativeness, native advertising, branded content, special project, communication strategy.</em></p>

Emotive Trending And Tracking of Tweets

2017 ◽  
Vol 7 (11) ◽  
pp. 25
Author(s):  
Sanjay Chhataru Gupta
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
The Social ◽  
The World ◽  
Complex Events

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.

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