scholarly journals Conceptual usage model of big data generated by social media

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Jolanta Sabaitytė ◽  
Roberta Karpovičiūtė
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Big Data ◽  
Data Analysis ◽  
Conceptual Model ◽  
Decision Support Tool ◽  
Virtual Space ◽  
Management Tools ◽  
Support Tool ◽  
Customer Profiles

The digital revolution and the communication platforms provided by the Web 2.0 virtual space era, such as social media, social networks, other tools and channels, create new opportunities for better marketing decisions based on user-generated data analysis. Every day customers of social media and other virtual tools are creating huge amounts of their actions-caused data, and businesses lack management tools supporting this process, which could create knowledge in the areas of deeper cognitive customer profiles and preferences. The growing number of social media users indicates the popularity of these communication tools among the information society, but science today lacks a deeper knowledge of social media-generated data and other algorithms for this kind of data usage. Therefore, the purpose of the article can be defined as the development of a conceptual model of big data generated by social media usage in business. The formation of the conceptual model is based on the analysis of big data assumptions and application possibilities, social media classification peculiarities and different channel specifics, identification of big data analysis methods and analysis of big data applications generated by social media. The conceptual model creates preconditions for deeper knowledge of user-generated big data in nowadays’ widely used communication platforms, as well as creation of the decision support tool for marketing specialists in order to use big data from social media in deeper cognitive customer profiles and preferences. The methods employed in this research are literature and other references analysis, synthesis and logical analysis of information, comparison of information, systemisation and visualisation.   Keywords: Big data, data mining, social media, social networks, internet marketing.

scholarly journals DIDŽIŲJŲ DUOMENŲ PANAUDOJIMAS SOCIALINĖJE MEDIJOJE / THE BIG DATA USE IN SOCIAL MEDIA

2019 ◽  
Vol 11 (0) ◽  
pp. 1-13
Author(s):  
Roberta Karpovičiūtė ◽  
Jolanta Sabaitytė
Keyword(s):  
Social Media ◽  
Big Data ◽  
Data Analysis ◽  
Conceptual Model ◽  
Large Data ◽  
Decision Support Tool ◽  
Virtual Space ◽  
Management Tools ◽  
Support Tool ◽  
Digital Revolution

The digital revolution and the communication platforms provided by the web 2.0 virtual space era, such as social media, social networks, other tools and channels, create new opportunities for better marketing decisions based on user-generated data analysis. Every day customers of social media and other virtual tools are creating huge amounts of their actions caused data, and business lack management tools for the support of this process, which could create knowledge in the area of customer profiles and preferences deeper cognition. Growing numbers of social media users indicate the popularity of these communication tools among the information society, but science today lacks a deeper knowledge of social media generated data and other algorithms for this data usage. Therefore, the purpose of the article is defined as the development of the conceptual model of big data generated by social media usage in business. The formation of the conceptual model is based on the analysis of big data assumptions and application possibilities, social media classification peculiarities and different channel specifics, identification of big data analysis methods and analysis of large data applications generated by social media. The conceptual model creates preconditions for deeper knowledge of user-generated big data in nowadays widely used communication platforms, as well as creation of the decision support tool for marketing specialists in order to use big data from social media in deeper customer profile and preferences cognition. Methods employed in this research are: literature and other references analysis, synthesis and logical analysis of information, comparison of information, systemization and visualization.

A Decision Support Tool for Evaluating Big Data Investment in Transport: Empirical evidence from European use cases of NOESIS project

2020 ◽  
Author(s):  
Christos Katrakazas ◽  
Natalia Sobrino ◽  
Ilias Trochidis ◽  
Jose Manuel Vassallo ◽  
Stratos Arampatzis ◽  
...  
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Empirical Evidence ◽  
Decision Support Tool ◽  
Use Cases ◽  
Support Tool

Video Advertising: Connection and differences between consumers?

2021 ◽  
Vol 3 (1) ◽  
pp. 14-25
Author(s):  
Sónia Ferreira ◽  
Sara Santos ◽  
Pedro Espírito Santo
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Literature Review ◽  
Conceptual Model ◽  
The Internet ◽  
Internet Search ◽  
Video Advertising ◽  
Social Media Engagement

The internet search trend has caused that online users are looking for more and more enriched information. The evolution of social media has been huge and users relate to social networks differently than they did before. Currently, there are more than 4 billion active users on social networks and brands are looking to showcase their products and services. Our research found the following factors that influence social media engagement: informativeness, self-connection and advertising stimulation. Through literature review, we propose a conceptual model that has been tested in the PLS-SEM. Data were collected from 237 consumers and our survey found that engagement in social media is explained by the variables identified by our model. Important contributions to brand theory and management will be found in this investigation.

An integrated parallel big data decision support tool using the W-CLUS-MCDA: A multi-scenario personnel assessment

2020 ◽  
Vol 195 ◽  
pp. 105749 ◽  
Author(s):  
Abtin Ijadi Maghsoodi ◽  
Dara Riahi ◽  
Enrique Herrera-Viedma ◽  
Edmundas Kazimieras Zavadskas
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Decision Support Tool ◽  
Support Tool ◽  
Personnel Assessment

Using enterprise social networks as a knowledge management tool in higher education

2017 ◽  
Vol 47 (4) ◽  
pp. 555-570 ◽  
Author(s):  
Niall Corcoran ◽  
Aidan Duane
Keyword(s):  
Higher Education ◽  
Social Networks ◽  
Social Media ◽  
Knowledge Sharing ◽  
Conceptual Model ◽  
Higher Education Institutions ◽  
Management Tool ◽  
Content Type ◽  
Enterprise Social Networks ◽  
Practical Implications

Purpose The management of organisational knowledge and the promotion of staff knowledge sharing are largely neglected in higher education institutions. The purpose of this study is to examine how enterprise social networks can enable staff knowledge sharing in communities of practice in that context. Design/methodology/approach The study is framed as an Action Research project, covering three cycles over a 12-month period. During the Diagnosing phase, a conceptual model was developed for empirical testing. Data were collected through 30 semi-structured interviews and a number of focus groups. This was supplemented by content analysis and reflective journaling. Findings The findings support the conceptual model and provide insight into the antecedents necessary for the creation of an enterprise social network-enabled knowledge-sharing environment, the motivators for and barriers to participation, and the perceived organisational and individual benefits of increased staff knowledge-sharing activity. Research limitations/implications As the study has a higher education focus, all of the findings may not be generalizable to other types of organisation. Further development of the conceptual model and testing in other contextual settings will yield greater generalizability. Practical implications A number of findings have practical implications for the management of higher education institutions, such as the evidence of a divide between faculty and other staff. In general, the study findings provide an opportunity for educationalists to better understand the scope and impact of employing social media platforms for knowledge sharing. Originality/value This paper adds to the growing body of work on organisational implementations of social media, and should be of interest to practitioners and researchers undertaking similar projects.

Sign in / Sign up

Export Citation Format

Share Document