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 TDSRC: A Task-Distributing System of Crowdsourcing Based on Social Relation Cognition

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Zhenlong Peng ◽  
Xiaolin Gui ◽  
Jian An ◽  
Ruowei Gui ◽  
Yali Ji
Keyword(s):  
Social Network ◽  
Problem Solving ◽  
Social Relation ◽  
Experimental Results ◽  
The Public ◽  
Trust Relationship ◽  
Main Challenge ◽  
The Social

Crowdsourcing significantly augments the creativity of the public and has become an indispensable component of many problem-solving pipelines. The main challenge, however, is the effective identification of malicious participators while distributing crowdsourcing tasks. In this paper, we propose a novel task-distributing system named Task-Distributing system of crowdsourcing based on Social Relation Cognition (TDSRC) to select qualified participators. First, we divided the tasks into categories according to task themes. Then, we constructed and calculated the Abilities Set (AS), Abilities Values (AVs), and the Friends’ Abilities Matrix (FAM) by using the historical interactive texts between a given task publisher (requester) and its friends. When a requester distributes a task, TDSRC can generate the candidate participators’ sequence based on the task needs and FAM. Finally, the best-matched friends in the sequence are selected as the task receivers (solvers), thus producing a personal FAM to disseminate the tasks. The experimental results indicate that (1) the proposed system can accurately and effectively discover the requester’s friends’ abilities and select appropriate solvers and (2) the natural trust relationship in the social network reduces fraudsters and enhances the quality of crowdsourcing services.

scholarly journals Identification of Influencers in eWord-of-Mouth communities using their Online Participation Features

2016 ◽  
Author(s):  
Sergio L. Toral ◽  
Maria Olmedilla ◽  
Francisco José Arenas-Márquez ◽  
M. Rocio Martinez-Torres
Keyword(s):  
Social Network ◽  
Online Social Network ◽  
Experimental Results ◽  
Purchasing Decisions ◽  
Trust Network ◽  
Online Participation ◽  
Meaningful Information

The identification of influencers in any type of online social network is of paramount importance, as they can significantly affect consumers’ purchasing decisions. This paper proposes the utilization of a self-designed web scraper to extract meaningful information for the identification of influencers and the analysis of how this new set of variables can be used to predict them. The experimental results from the Ciao UK website will be used to illustrate the proposed approach and to provide new insights in the identification of influencers. Obtained results show the importance of the trust network, but considering the intensity and the quality of both trustors and trustees.

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.

Extraverts Have Larger Social Network Layers

2011 ◽  
Vol 32 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Thomas V. Pollet ◽  
Sam G. B. Roberts ◽  
Robin I. M. Dunbar
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Outer Layer ◽  
Network Size ◽  
Emotional Intensity ◽  
Emotional Closeness ◽  
Network Layer ◽  
Network Layers ◽  
Social Network Size

Previous studies showed that extraversion influences social network size. However, it is unclear how extraversion affects the size of different layers of the network, and how extraversion relates to the emotional intensity of social relationships. We examined the relationships between extraversion, network size, and emotional closeness for 117 individuals. The results demonstrated that extraverts had larger networks at every layer (support clique, sympathy group, outer layer). The results were robust and were not attributable to potential confounds such as sex, though they were modest in size (raw correlations between extraversion and size of network layer, .20 < r < .23). However, extraverts were not emotionally closer to individuals in their network, even after controlling for network size. These results highlight the importance of considering not just social network size in relation to personality, but also the quality of relationships with network members.

Hybrid features prediction model of movie quality using Multi-machine learning techniques for effective business resource planning

2021 ◽  
Vol 40 (5) ◽  
pp. 9361-9382 ◽  
Author(s):  
Naeem Iqbal ◽  
Rashid Ahmad ◽  
Faisal Jamil ◽  
Do-Hyeun Kim
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Resource Planning ◽  
Experimental Results ◽  
Quality Prediction ◽  
Classification Models ◽  
Hybrid Features ◽  
Social Media Data ◽  
Media Data

Quality prediction plays an essential role in the business outcome of the product. Due to the business interest of the concept, it has extensively been studied in the last few years. Advancement in machine learning (ML) techniques and with the advent of robust and sophisticated ML algorithms, it is required to analyze the factors influencing the success of the movies. This paper presents a hybrid features prediction model based on pre-released and social media data features using multiple ML techniques to predict the quality of the pre-released movies for effective business resource planning. This study aims to integrate pre-released and social media data features to form a hybrid features-based movie quality prediction (MQP) model. The proposed model comprises of two different experimental models; (i) predict movies quality using the original set of features and (ii) develop a subset of features based on principle component analysis technique to predict movies success class. This work employ and implement different ML-based classification models, such as Decision Tree (DT), Support Vector Machines with the linear and quadratic kernel (L-SVM and Q-SVM), Logistic Regression (LR), Bagged Tree (BT) and Boosted Tree (BOT), to predict the quality of the movies. Different performance measures are utilized to evaluate the performance of the proposed ML-based classification models, such as Accuracy (AC), Precision (PR), Recall (RE), and F-Measure (FM). The experimental results reveal that BT and BOT classifiers performed accurately and produced high accuracy compared to other classifiers, such as DT, LR, LSVM, and Q-SVM. The BT and BOT classifiers achieved an accuracy of 90.1% and 89.7%, which shows an efficiency of the proposed MQP model compared to other state-of-art- techniques. The proposed work is also compared with existing prediction models, and experimental results indicate that the proposed MQP model performed slightly better compared to other models. The experimental results will help the movies industry to formulate business resources effectively, such as investment, number of screens, and release date planning, etc.

Conical SNA using fuzzy k-medoids based on user experience

2021 ◽  
pp. 002072092098849
Author(s):  
Poonam Rani ◽  
MPS Bhatia ◽  
Devendra K Tayal
Keyword(s):  
Social Networks ◽  
Social Network ◽  
User Experience ◽  
Three Dimensional ◽  
Experimental Results ◽  
Dynamic Parameters ◽  
Clustering Method ◽  
Cone Model ◽  
Intelligent Approach ◽  
Conical Model

The paper presents an intelligent approach for the comparison of social networks through a cone model by using the fuzzy k-medoids clustering method. It makes use of a geometrical three-dimensional conical model, which astutely represents the user experience views. It uses both the static as well as the dynamic parameters of social networks. In this, we propose an algorithm that investigates which social network is more fruitful. For the experimental results, the proposed work is employed on the data collected from students from different universities through the Google forms, where students are required to rate their experience of using different social networks on different scales.

scholarly journals Identification of the State of Electrical Appliances with the Use of a Pulse Signal Generator

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 673
Author(s):  
Augustyn Wójcik ◽  
Piotr Bilski ◽  
Robert Łukaszewski ◽  
Krzysztof Dowalla ◽  
Ryszard Kowalik
Keyword(s):  
Measurement System ◽  
Cross Correlation ◽  
Pulse Signal ◽  
Signal Generator ◽  
Experimental Results ◽  
The Novel ◽  
End User ◽  
Standard Classification ◽  
Electrical Appliance

The paper presents the novel HF-GEN method for determining the characteristics of Electrical Appliance (EA) operating in the end-user environment. The method includes a measurement system that uses a pulse signal generator to improve the quality of EA identification. Its structure and the principles of operation are presented. A method for determining the characteristics of the current signals’ transients using the cross-correlation is described. Its result is the appliance signature with a set of features characterizing its state of operation. The quality of the obtained signature is evaluated in the standard classification task with the aim of identifying the particular appliance’s state based on the analysis of features by three independent algorithms. Experimental results for 15 EAs categories show the usefulness of the proposed approach.

scholarly journals Together, We Can Make This Place Our Home: Civic Engagement Among Asian Immigrants

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 99-99
Author(s):  
Cindy Bui ◽  
Kyungmin Kim ◽  
Qian Song ◽  
Yuri Jang
Keyword(s):  
Social Network ◽  
Civic Engagement ◽  
Asian American ◽  
American Culture ◽  
City Council ◽  
Asian Immigrants ◽  
The City ◽  
The U.S ◽  
Acculturation Factors

Abstract Civic engagement is an important dimension of age-friendly communities but has been understudied among Asian immigrant groups. While research has attributed greater civic engagement among immigrants to acculturation factors, the influence of acculturation may be conditioned upon Asian immigrants’ social network and place attachment to their city. We used data from the Asian American Quality of Life survey to analyze civic engagement activity (e.g., City council meeting, voting in a City election) among a diverse sample of middle-aged and older Asian immigrants in Austin, Texas (N = 994). 34.5% of the sample had participated in at least one civic engagement activity in the past 12 months. We examined how such civic engagement is associated with acculturation factors, and further examined whether one’s friend network and perception of their city moderated the association. We found that number of years lived in the U.S., familiarity with mainstream American culture, and number of friends in one’s social network were positively related to civic engagement activity. Furthermore, we found that the association between years lived in the U.S. and civic engagement was more pronounced for immigrants with larger friend networks; the association between familiarity with American culture and civic engagement was more pronounced for immigrants with more positive perceptions of the city. These findings highlight that acculturation may not operate alone in civic engagement among Asian immigrants. Rather, it may also be important to create opportunities for Asian immigrants to feel connected to their community and build meaningful friend networks to encourage civic engagement.

scholarly journals Contour Detection for Fibre of Preserved Szechuan Pickle Based on Dilated Convolution

2019 ◽  
Vol 9 (13) ◽  
pp. 2684 ◽  
Author(s):  
Hongyang Li ◽  
Lizhuang Liu ◽  
Zhenqi Han ◽  
Dan Zhao
Keyword(s):  
Edge Detection ◽  
State Of The Art ◽  
Contour Detection ◽  
Experimental Results ◽  
Contour Method ◽  
Class Differences ◽  
Dilated Convolution ◽  
The Mean ◽  
Art Performance

Peeling fibre is an indispensable process in the production of preserved Szechuan pickle, the accuracy of which can significantly influence the quality of the products, and thus the contour method of fibre detection, as a core algorithm of the automatic peeling device, is studied. The fibre contour is a kind of non-salient contour, characterized by big intra-class differences and small inter-class differences, meaning that the feature of the contour is not discriminative. The method called dilated-holistically-nested edge detection (Dilated-HED) is proposed to detect the fibre contour, which is built based on the HED network and dilated convolution. The experimental results for our dataset show that the Pixel Accuracy (PA) is 99.52% and the Mean Intersection over Union (MIoU) is 49.99%, achieving state-of-the-art performance.

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