scholarly journals The centrality of ethical utterances within professional narratives

2021 ◽  
pp. 103237322110402
Author(s):  
Dean Neu ◽  
Gregory D. Saxton ◽  
Jeffery Everett ◽  
Abu Rahaman
Keyword(s):  
Social Network ◽  
Topic Modeling ◽  
Professional Behavior ◽  
Professional Conduct ◽  
Professional Journal ◽  
Ethical Discourse ◽  
Canadian Institute ◽  
Modeling Techniques ◽  
Chartered Accountants ◽  
Over Time

This study examines the centrality of ethics within editorials published in the Canadian Institute of Chartered Accountants’ professional journal, CA Magazine, over the 1912 to 2010 period. Starting from the twin assumptions that editorials speak about appropriate professional behavior using a variety of words such as ‘ethics,’ ‘conduct,’ and ‘codes,’ and that appropriate professional behavior is situational, we use topic modeling techniques to identify these dimensions of ethical discourse. We then use social network analysis methods to map the position and centrality of ethics within the editorials across time. The results show that enunciations about appropriate professional conduct are broader than simply enunciations using the word ‘ethics’. The results also highlight that ethical utterances become more central, not less central, over time.

Professional Conduct

2013 ◽  
Author(s):  
Ann A. Abbott
Keyword(s):  
Social Workers ◽  
Dispute Resolution ◽  
Review Process ◽  
Code Of Ethics ◽  
Professional Behavior ◽  
Professional Conduct ◽  
Professional Misconduct ◽  
Alternate Dispute Resolution ◽  
Professional Review ◽  
Over Time

The professional review process delineates procedures for hearing complaints of alleged professional misconduct by members of the National Association of Social Workers (NASW). It provides mechanisms for conducting hearings and alternate dispute resolution via mediation, monitoring professional behavior, and sanctioning and developing corrective actions for NASW members who are in violation of the NASW’s Code of Ethics. The process, originally developed in 1967, has been modified over time to reflect the best identified means for conducting fair hearings and carrying out the most appropriate interventions.

scholarly journals Relacionando Modelagem de Tópicos e Classificação de Sentimentos para Análise de Mensagens do Twitter Durante a Pandemia da COVID-19

2020 ◽  
Author(s):  
Matheus Adler Soares Pinto ◽  
Antonio Fernando Lavareda Jacob Junior ◽  
Antonio José G. Busson ◽  
Sérgio Colcher
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Sentiment Analysis ◽  
Topic Modeling ◽  
The Social ◽  
Modeling Techniques ◽  
Medical Advances

In 2020, COVID-19 pandemic is one of the most talked-about subjects on social networks. This subject has generated discussions of great importance about politics, economics, medical advances, people’s awareness, preventive techniques, etc. Using sentiment analysis and topic modeling techniques, in this paper, we aim to present an analysis of the messages from the social network Twitter during the pandemic of COVID-19. For this, we use a tweets dataset to train a sentiment classifier and then use the NMF algorithm to perform the interest topic generation.

Developing a sustainable Digital Health Innovation Ecosystem in a rural and resource-poor region: A monitored networking approach (Preprint)

2020 ◽  
Author(s):  
Arunangsu Chatterjee ◽  
Sebastian Stevens ◽  
Sheena Asthana ◽  
Ray B Jones
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Data Collection ◽  
Digital Health ◽  
Resource Poor Setting ◽  
Quadruple Helix ◽  
Innovation Ecosystem ◽  
Resource Poor ◽  
Quadruple Helix Model ◽  
Over Time

BACKGROUND Digital health (DH) innovation ecosystems (IE) are key to the development of new e-health products and services. Within an IE, third parties can help promote innovation by acting as knowledge brokers and the conduits for developing inter-organisational and interpersonal relations, particularly for smaller organisations. Kolehmainen’s quadruple helix model suggests who the critical IE actors are, and their roles. Within an affluent and largely urban setting, such ecosystems evolve and thrive organically with minimal intervention due to favourable economic and geographical conditions. Facilitating and sustaining a thriving DH IE within a resource-poor setting can be far more challenging even though far more important for such peripheral economics and the health and well-being of those communities. OBJECTIVE Taking a rural and remote region in the UK, as an instance of an IE in a peripheral economy, we adapt the quadruple helix model of innovation, apply a monitored social networking approach using McKinsey’s Three Horizons of growth to explore: • What patterns of connectivity between stakeholders develop within an emerging digital health IE? • How do networks develop over time in the DH IE? • In what ways could such networks be nurtured in order to build the capacity, capability and sustainability of the DH IE? METHODS Using an exploratory single case study design for a developing digital health IE, this study adopts a longitudinal social network analysis approach, enabling the authors to observe the development of the innovation ecosystem over time and evaluate the impact of targeted networking interventions on connectivity between stakeholders. Data collection was by an online survey and by a novel method, connection cards. RESULTS Self-reported connections between IE organisations increased between the two waves of data collection, with Small and Medium-sized Enterprises (SMEs) and academic institutions the most connected stakeholder groups. Patients involvement improved over time but still remains rather peripheral to the DH IE network. Connection cards as a monitoring tool worked really well during large events but required significant administrative overheads. Monitored networking information categorised using McKinsey’s Three Horizons proved to be an effective way to organise networking interventions ensuring sustained engagement. CONCLUSIONS The study reinforces the difficulty of developing and sustaining a DH IE in a resource-poor setting. It demonstrates the effective monitored networking approach supported by Social Network Analysis allows to map the networks and provide valuable information to plan future networking interventions (e.g. involving patients or service users). McKinsey’s Three Horizons of growth-based categorisation of the networking assets help ensure continued engagement in the DH IE contributing towards its long-term sustainability. Collecting ongoing data using survey or connection card method will become more labour intensive and ubiquitous ethically driven data collection methods can be used in future to make the process more agile and responsive.

A CHRONOLOGY OF THE DEVELOPMENT OF CORPORATE FINANCIAL REPORTING IN CANADA: 1850 TO 1983

1986 ◽  
Vol 13 (1) ◽  
pp. 31-62 ◽  
Author(s):  
George J. Murphy
Keyword(s):  
Financial Reporting ◽  
The United States ◽  
Company Law ◽  
Economic Relationships ◽  
Professional Activities ◽  
Financial Reporting Standards ◽  
Significant Events ◽  
Canadian Institute ◽  
Chartered Accountants ◽  
Corporate Financial Reporting

A chronology of significant events in the development of corporate financial reporting standards and practices is presented. The introductory comments to the various sections direct attention to some of the main patterns and trends in that development and provide the framework in which the listing of events is to be interpreted. The particularly significant domestic sources of influence are the legislative and professional activities in Ontario and, in more recent times, the activities of the Canadian Institute of Chartered Accountants. External influences have been—not unexpectedly—the traditions of English Company law and the close professional, institutional and economic relationships with the United States. Some internationally significant developments unique to Canada are indicated.

A network case of knowledge brokering

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Joelle Rodway ◽  
Stephen MacGregor ◽  
Alan Daly ◽  
Yi-Hwa Liou ◽  
Susan Yonezawa ◽  
...  
Keyword(s):  
Social Network ◽  
Learning Community ◽  
Knowledge Exchange ◽  
Point Of View ◽  
Network Activity ◽  
Centrality Measures ◽  
Knowledge Brokering ◽  
Content Type ◽  
Knowledge Brokers ◽  
Over Time

PurposeThe purpose of this paper is two-fold: (1) to offer a conceptual understanding of knowledge brokering from a sociometric point-of-view; and (2) to provide an empirical example of this conceptualization in an education context.Design/methodology/approachWe use social network theory and analysis tools to explore knowledge exchange patterns among a group of teachers, instructional coaches and administrators who are collectively seeking to build increased capacity for effective mathematics instruction. We propose the concept of network activity to measure direct and indirect knowledge brokerage through the use of degree and betweenness centrality measures. Further, we propose network utility—measured by tie multiplexity—as a second key component of effective knowledge brokering.FindingsOur findings suggest significant increases in both direct and indirect knowledge brokering activity across the network over time. Teachers, in particular, emerge as key knowledge brokers within this networked learning community. Importantly, there is also an increase in the number of resources exchanged through network relationships over time; the most active knowledge brokers in this social ecosystem are those individuals who are exchanging multiple forms of knowledge.Originality/valueThis study focuses on knowledge brokering as it presents itself in the relational patterns among educators within a social ecosystem. While it could be that formal organizational roles may encapsulate knowledge brokering across physical structures with an education system (e.g. between schools and central offices), these individuals are not necessarily the people who are most effectively brokering knowledge across actors within the broader social network.

scholarly journals Temporal Activity Path Based Character Correction in Heterogeneous Social Networks via Multimedia Sources

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Jun Long ◽  
Lei Zhu ◽  
Zhan Yang ◽  
Chengyuan Zhang ◽  
Xinpan Yuan
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Large Scale ◽  
Multimedia Data ◽  
Attribute Information ◽  
Novel Method ◽  
Relationship Network ◽  
Heterogeneous Social Networks ◽  
The Relationship ◽  
Over Time

Vast amount of multimedia data contains massive and multifarious social information which is used to construct large-scale social networks. In a complex social network, a character should be ideally denoted by one and only one vertex. However, it is pervasive that a character is denoted by two or more vertices with different names; thus it is usually considered as multiple, different characters. This problem causes incorrectness of results in network analysis and mining. The factual challenge is that character uniqueness is hard to correctly confirm due to lots of complicated factors, for example, name changing and anonymization, leading to character duplication. Early, limited research has shown that previous methods depended overly upon supplementary attribute information from databases. In this paper, we propose a novel method to merge the character vertices which refer to the same entity but are denoted with different names. With this method, we firstly build the relationship network among characters based on records of social activities participating, which are extracted from multimedia sources. Then we define temporal activity paths (TAPs) for each character over time. After that, we measure similarity of the TAPs for any two characters. If the similarity is high enough, the two vertices should be considered as the same character. Based on TAPs, we can determine whether to merge the two character vertices. Our experiments showed that this solution can accurately confirm character uniqueness in large-scale social network.

Quantifying Virality of Information in Online Social Networks

2012 ◽  
Vol 4 (1) ◽  
pp. 32-45 ◽  
Author(s):  
Abhishek Vaish ◽  
Rajiv Krishna G. ◽  
Akshay Saxena ◽  
Dharmaprakash M. ◽  
Utkarsh Goel
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Online Social Network ◽  
Critical Factors ◽  
Asset Valuation ◽  
Valuation Technique ◽  
Information Item ◽  
Viral Nature ◽  
Over Time

The aim of this research is to propose a model through which the viral nature of an information item in an online social network can be quantified. Further, the authors propose an alternate technique for information asset valuation by accommodating virality in it which not only complements the existing valuation system, but also improves the accuracy of the results. They use a popularly available YouTube dataset to collect attributes and measure critical factors such as share-count, appreciation, user rating, controversiality, and comment rate. These variables are used with a proposed formula to obtain viral index of each video on a given date. The authors then identify a conventional and a hybrid asset valuation technique to demonstrate how virality can fit in to provide accurate results.The research demonstrates the dependency of virality on critical social network factors. With the help of a second dataset acquired, the authors determine the pattern virality of an information item takes over time.

scholarly journals On Building an Interpretable Topic Modeling Approach for the Urdu Language

2020 ◽  
Author(s):  
Zarmeen Nasim
Keyword(s):  
Feature Extraction ◽  
Deep Learning ◽  
Topic Modeling ◽  
Language Modeling ◽  
Low Resource ◽  
Modeling Approach ◽  
Part Of Speech ◽  
Modeling Techniques ◽  
Pos Tagger

This research is an endeavor to combine deep-learning-based language modeling with classical topic modeling techniques to produce interpretable topics for a given set of documents in Urdu, a low resource language. The existing topic modeling techniques produce a collection of words, often un-interpretable, as suggested topics without integrat-ing them into a semantically correct phrase/sentence. The proposed approach would first build an accurate Part of Speech (POS) tagger for the Urdu Language using a publicly available corpus of many million sentences. Using semanti-cally rich feature extraction approaches including Word2Vec and BERT, the proposed approach, in the next step, would experiment with different clus-tering and topic modeling techniques to produce a list of potential topics for a given set of documents. Finally, this list of topics would be sent to a labeler module to produce syntactically correct phrases that will represent interpretable topics.

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