scholarly journals ADVO: A System to Manage Influencer Marketing Campaigns on Social Networks

2021 ◽  
Vol 11 (14) ◽  
pp. 6497
Author(s):  
Tai Huynh ◽  
Hien D. Nguyen ◽  
Ivan Zelinka ◽  
Kha V. Nguyen ◽  
Vuong T. Pham ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Real Time ◽  
Management System ◽  
Digital Marketing ◽  
Information Propagation ◽  
Content Creation ◽  
Marketing Campaign ◽  
Commercial Activities ◽  
Technology Revolution

In the fourth technology revolution, influencer marketing is an essential kind of digital marketing. This marketing uses identified influencers to viral the information of products to target customers. It is useful to support brands exposed to more valuable online consumers. The influencer marketing campaign needs a management system to manage on a social network. This system helps to increase the efficiency of a campaign. This paper proposes a management system for the influencer marketing campaign, called the ADVO system. This system provides a tool for collecting data on a social network and detecting potential brand influencers for the marketing campaign. The meaningful measures for users include amplification factors for evaluating the information propagation, the passion point to measure a user’s favorite when it comes to a brand, and the content creation score for determining the ability of post-content creating. The ADVO system helps the brand to make the decision through real-time visual reports of the campaign. It is a foundation to create commercial activities and construct an advocate community of the related brand.

scholarly journals The Clubhouse Phenomenon: Do We Need Another Social Network?

2021 ◽  
Author(s):  
Wadim Strielkowski
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Networking ◽  
Real Time ◽  
Group Psychotherapy ◽  
Text Messages ◽  
Online Video ◽  
Conference Call ◽  
Start Up ◽  
Further Development

Being a combination of the conference call, talkback radio, audio podcast, and an online video chat, Clubhouse is a new social networking app that gained over 10 million users and over $100 in valuation in just 8 months. Unlike other social networks, it offers a real-time streaming audio chat that does not ask users to share any unnecessary information like exchanging text messages, conducting video calls, or sharing photos. Instead, Clubhouse users can listen to real-time conversations, contribute to these conversations and create their own conversations for the others to listen and to interact with. Often nicknamed a “Silicon Valley’s hottest start-up”, Clubhouse positions itself as an “exclusive” and “alternative” social network that attracts various celebrities and people who just want to talk to each other. Launched in March 2020, amidst the COVID-19 pandemic with its social distancing and lockdowns, Clubhouse offered its users a space for the digital group psychotherapy where people could solve their problems by talking them through with strangers. However, it is unclear what is going to happen to this new social network in the post-pandemic world after all of its hype eventually evaporates. This paper discusses the possible underlying motives for the Clubhouse creation and its real purposes. Moreover, it looks at the three possible scenarios of its further development.

Measure of the Content Creation Score on Social Network Using Sentiment Score and Passion Point

2020 ◽  
Author(s):  
Hien D. Nguyen ◽  
Tai Huynh ◽  
Son T. Luu ◽  
Suong N. Hoang ◽  
Vuong T. Pham ◽  
...  
Keyword(s):  
Social Network ◽  
Experimental Results ◽  
Information Propagation ◽  
Content Creation ◽  
Sentiment Score

Social network is one of efficient tools for spreading information. The evaluation of the content creation of a user is a useful feature to improve the ability of information propagation on social network. In this paper, the measures for evaluating the user’s content creation are proposed. They include the passion point of a user with a brand and the quality of the user’s posts. The passion point is computed based on the sentiment score of posting and the activity of the user. The quality of the user’s posts is computed through the analyzing of the post’s content. Those measures are combined to analyze the interesting of posts. The proposed method has been tested and get the positive experimental results.

scholarly journals Detecting the Influencer on Social Networks Using Passion Point and Measures of Information Propagation †

2020 ◽  
Vol 12 (7) ◽  
pp. 3064 ◽  
Author(s):  
Tai Huynh ◽  
Hien Nguyen ◽  
Ivan Zelinka ◽  
Dac Dinh ◽  
Xuan Hau Pham
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Marketing Strategy ◽  
Online Social Network ◽  
Modern Method ◽  
Information Propagation ◽  
The Social ◽  
User Data ◽  
The Impact ◽  
Positive Results

Influencer marketing is a modern method that uses influential users to approach goal customers easily and quickly. An online social network is a useful platform to detect the most effective influencer for a brand. Thus, we have an issue: how can we extract user data to determine an influencer? In this paper, a model for representing a social network based on users, tags, and the relationships among them, called the SNet model, is presented. A graph-based approach for computing the impact of users and the speed of information propagation, and measuring the favorite brand of a user and sharing the similar brand characteristics, called a passion point, is proposed. Therefore, we consider two main influential measures, including the extent of the influence on other people by the relationships between users and the concern to user’s tags, and the tag propagation through social pulse on the social network. Based on these, the problem of determining the influencer of a specific brand on a social network is solved. The results of this method are used to run the influencer marketing strategy in practice and have obtained positive results.

Crowd attraction-driven community evolution on social network

2021 ◽  
pp. 2250009
Author(s):  
Fuzhong Nian ◽  
Li Luo ◽  
Xuelong Yu
Keyword(s):  
Social Networks ◽  
Community Structure ◽  
Social Network ◽  
Large Scale ◽  
Detection Algorithm ◽  
Information Propagation ◽  
Evolution Analysis ◽  
Dynamic Social Networks ◽  
Community Evolution ◽  
Community Detection Algorithm

The evolution analysis of community structure of social network will help us understand the composition of social organizations and the evolution of society better. In order to discover the community structure and the regularity of community evolution in large-scale social networks, this paper analyzes the formation process and influencing factors of communities, and proposes a community evolution analysis method of crowd attraction driven. This method uses the traditional community division method to divide the basic community, and introduces the theory of information propagation into complex network to simulate the information propagation of dynamic social networks. Then defines seed node, the activity of basic community and crowd attraction to research the influence of groups on individuals in social networks. Finally, making basic communities as fixed groups in the network and proposing community detection algorithm based on crowd attraction. Experimental results show that the scheme can effectively detect and identify the community structure in large-scale social networks.

scholarly journals MARKETING COMMUNICATION MODEL FOR SOCIAL NETWORKS

2018 ◽  
Vol 19 (3) ◽  
pp. 500-520
Author(s):  
Martin Klepek ◽  
Halina Starzyczná
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Resistance To Change ◽  
Online Advertising ◽  
Communication Model ◽  
Marketing Communication ◽  
Content Creation ◽  
The Social ◽  
Communication Needs

The advent of social media offers yet another set of communication channels which can brand add to integrated marketing communication strategies. Contrary to online advertising available on social media where traditional advertising logic provides an adequate explanation, the content creation and dialogue on social networks still lack sufficient understanding. Consequently, there are many companies which tend to misunderstand customers communication needs within the social media landscape. The obvious reason is the lack of knowledge combined with resistance to change. To bridge this gap, there is a need for empirical research which will clarify the current communication needs of customers. To explore this phenomenon, exploratory research employing questionnaire involving 481 respondents was evaluated with factor analysis method. Identification of three factors provided deeper insights into the understanding of attitudes and behaviour of the current internet population in the Czech Republic. Social network Facebook was chosen as the most widespread not only locally but also globally. Based on this research and previous research studies on communication, a new communication model is proposed in which the element of interaction is the most important. The proposed scheme bears some novel aspects. Firstly, the content in our model is not created outside as in previous models. A social network itself provides a platform for content creation. Secondly, we expanded the physical technical environment of the social network by the abstract brand community in which not only customers but the employees form a vital part. Lastly, the data plays an important role as a valuable tool for feedback and further analysis. Data flow from customer to company enables managers to execute true mass individualisation.

scholarly journals A trust model for spreading gossip in social networks: a multi-type bootstrap percolation model

2020 ◽  
Vol 476 (2235) ◽  
pp. 20190826 ◽  
Author(s):  
Rinni Bhansali ◽  
Laura P. Schaposnik
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Trust Model ◽  
Percolation Model ◽  
Marketing Strategies ◽  
Bootstrap Percolation ◽  
Information Propagation ◽  
Fake News ◽  
Minimum Threshold ◽  
Bp Model

We introduce here a multi-type bootstrap percolation model, which we call T -Bootstrap Percolation ( T -BP), and apply it to study information propagation in social networks. In this model, a social network is represented by a graph G whose vertices have different labels corresponding to the type of role the person plays in the network (e.g. a student, an educator etc.). Once an initial set of vertices of G is randomly selected to be carrying a gossip (e.g. to be infected), the gossip propagates to a new vertex provided it is transmitted by a minimum threshold of vertices with different labels. By considering random graphs, which have been shown to closely represent social networks, we study different properties of the T -BP model through numerical simulations, and describe its implications when applied to rumour spread, fake news and marketing strategies.

scholarly journals The Spammer Detection and Fake User Identification on Social Networks

2021 ◽  
Vol 9 (11) ◽  
pp. 87-92
Author(s):  
Dr. C. K. Gomathy
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Real Time ◽  
Online Social Network ◽  
User Identification ◽  
Online Source

Abstract: The Twitter has fleetly come an online source for acquiring real- time his/ her information about druggies. Twitter is an Online Social Network (OSN) where druggies can partake anything and everything, similar as news, opinions, and indeed their moods. Several arguments can be held over different motifs, similar as politics, Perticular affairs, and important events. When a stoner tweets commodity, it's incontinently conveyed to her followers, allowing them to unfold the entered information at a much broader position. With the elaboration of OSNs, the need to study and dissect druggies' actions in online social platforms has intensity Spammers can be linked grounded on (i) fake content, (ii) URL grounded spam discovery, (iii) spam in trending motifs, and (iv) fake stoner identification. And with the help of machine literacy algorithms we're going to identify the fake stoner and spammer in twitter. Keywords: Online Social Network, Spammers Identification, Fake User Identification.

Big Data Analytics of Geo-Social Media on Planning and Real-Time Decisions

2019 ◽  
Vol 16 (8) ◽  
pp. 3332-3337 ◽  
Author(s):  
S. Dhamodaran ◽  
G. Mahalakshmi ◽  
P. Harika ◽  
J. Refonaa ◽  
K. AshokKumar
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Big Data ◽  
Social Network ◽  
Real Time ◽  
Spatial Data ◽  
System Throughput ◽  
Future Planning ◽  
Efficient System ◽  
International Conference

The authorities are to be considered to make a real-time decision and future planning by various analyzing geo-social media posts in Geo-social Network. However, there are millions of Geo-social Network users who are producing overwhelming of data, called “Big Data” that is challenging to be analyzed and make the required real-time decisions. In our proposed system proposal of the efficient system for inquiring Geo-social Networks and harvesting the data as well as user’s location information (Dhamodaran, S. and Lakshmi, M., 2017. Design and Analysis of Spatial-Temporal Model Using Hydrological Techniques. IEEE International Conference on Computing of Power, Energy and Communication. pp.1–4). System architecture is proposed that processes an abundant amount of various social networks’ of data to monitor. Earth events, incidents, medical diseases, user trends, and views to make future real-time decisions and facilitate future planning (Dhamodarn, S., et al., Identification of User Poi in Spatial Data Using Android Application. International Conference on Computation of Power, Energy Information and Communication (ICCPEIC), IEEE. ISBN: 978-1-5090-0901-5). Twitter and Flickr have been analyzed using the proposed architecture in order to identify current events or disasters, such as earthquakes, snow, Ebola virus, and fires. The system is evaluated with respect to an efficiency of data while considering the system throughput.

scholarly journals Motivations of youth audiences to content creation and dissemination on social network sites

2019 ◽  
Vol 25 (2) ◽  
pp. 915-933
Author(s):  
Mª Cruz López de Ayala López ◽  
Pedro Paniagua Santamaría
Keyword(s):  
Social Networks ◽  
Factor Analysis ◽  
Social Network ◽  
Young People ◽  
Social Network Sites ◽  
Uses And Gratifications Theory ◽  
Content Creation ◽  
Different Types ◽  
Very High ◽  
Different Levels

Young people show very high and intensive levels of social networks use. However, users have different levels of involvement as regards their degree of interactivity in these platforms. Supported by uses and gratifications theory and applying a factor analysis, the motivations that explain their participation in several profiles of social networks and differences between those who do and those who do not comment are analysed. Based on a self-administered survey of 461 young university students, the main conclusions include the diversity of nuances in the combinations of reasons that explain participation in different types of profiles on social networks; particularly worth highlighting are the similarities between profiles of NGOs and those of celebrities. Also of note is the tendency of users who comment on commercial, political, social and leisure profiles to display motivations linked to searching for information, being useful, influencing others, interacting and showing adhesion, depending on the sphere.

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