scholarly journals Analysis on Health Information Acquisition of Social Network Users by Opinion Mining: Case Analysis Based on the Discussion on COVID-19 Vaccinations

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Datian Bi ◽  
Jingyuan Kong ◽  
Xue Zhang ◽  
Junli Yang

This study aims to explore phenomena and laws that occur when different users on social network platforms obtain health information by constructing an opinion mining model, analyzing the user’s position on selected cases, and exploring the reflection of the phenomenon of truth decay on platforms. It selects group posts regarding the COVID-19 vaccination dispute on the Douban platform, analyzes the positions of different users, and explores phenomena related to users obtaining health information on domestic social platforms according to different topics and information behaviors. The results reveal a linear relationship between the negative and neutral attitudes of netizens on social networking platforms. Moreover, netizens tend to hold subjective language when expressing their views and attitudes, and their views on social platforms will not change easily. The study explores the health information acquisition behavior of netizens on social platforms based on the constructed user opinion mining model. The study is helpful for relevant units and platforms to make scientific decisions and provide guidance according to different positions of Internet users.

1970 ◽  
pp. 237-260
Author(s):  
Jolanta Jarczyńska

Social networking sites (SNS), popularly called portals, are sites that combine multiple functions. Users might communicate by SNS with their friends, share photos and movies or participate in groups. SNS satisfy their users’ needs such as the need to connect or to self-present. These functions of SNS make them attractive. It is not surprising, therefore, that in recent years there has been an increasing number of people, especially young ones, using social networking sites. Facebook (FB)is the most popular social network in the world. Statistics carried out by FB indicate a rapid increase in the number of Internet users who make use of this particular social networking site. The article presents the characteristics of the phenomenon of school students’ excessive use of social networking sites. It defines the basic concepts, describes the diagnostic criteria for abuse of social networking sites and theories to explain this behavior. It shows the loss and benefits of excessive use of social networks and presents tools used in research to measure school students’ excessive use ofsocial networking sites.


2017 ◽  
Vol 9 (2) ◽  
pp. 28 ◽  
Author(s):  
Amita Jain ◽  
Minni Jain

Sentiment analysis research of public information from social networking sites has been increasing immensely in recent years. Data available at social networking sites is one of the most effective and accurate source to identify the public sentiment of any product/service. In this paper, we propose a novel localized opinion mining model based on common sense information extracted from ConceptNet ontology. The proposed methodology allows interpretation and utilization of data extracted from social media site “Twitter” to identify public opinions. This paper includes location specific, male- female specific and concept specific popularities of product. All extracted concepts are used to calculate senti_score and to build a machine learning model that classifies the user opinions as positive or negative.


2019 ◽  
Vol 13 (2) ◽  
pp. 159-165
Author(s):  
Manik Sharma ◽  
Gurvinder Singh ◽  
Rajinder Singh

Background: For almost every domain, a tremendous degree of data is accessible in an online and offline mode. Billions of users are daily posting their views or opinions by using different online applications like WhatsApp, Facebook, Twitter, Blogs, Instagram etc. Objective: These reviews are constructive for the progress of the venture, civilization, state and even nation. However, this momentous amount of information is useful only if it is collectively and effectively mined. Methodology: Opinion mining is used to extract the thoughts, expression, emotions, critics, appraisal from the data posted by different persons. It is one of the prevailing research techniques that coalesce and employ the features from natural language processing. Here, an amalgamated approach has been employed to mine online reviews. Results: To improve the results of genetic algorithm based opining mining patent, here, a hybrid genetic algorithm and ontology based 3-tier natural language processing framework named GAO_NLP_OM has been designed. First tier is used for preprocessing and corrosion of the sentences. Middle tier is composed of genetic algorithm based searching module, ontology for English sentences, base words for the review, complete set of English words with item and their features. Genetic algorithm is used to expedite the polarity mining process. The last tier is liable for semantic, discourse and feature summarization. Furthermore, the use of ontology assists in progressing more accurate opinion mining model. Conclusion: GAO_NLP_OM is supposed to improve the performance of genetic algorithm based opinion mining patent. The amalgamation of genetic algorithm, ontology and natural language processing seems to produce fast and more precise results. The proposed framework is able to mine simple as well as compound sentences. However, affirmative preceded interrogative, hidden feature and mixed language sentences still be a challenge for the proposed framework.


2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S412-S412
Author(s):  
Bo Xie ◽  
Kristina Shiroma

Abstract Older adults living in Asia or of Asian origin have unique preferences for information that require special attention. This symposium focuses on the health information preferences and behaviors of Asian older adults. Song et al. investigated the relationship between Internet use and perceived loneliness among Older Chinese using from survey data collected in the 2015 wave of the China Health and Retirement Longitudinal Study (CHARLS), a national study involving 12,400 households in Mainland China. Multiple regression results suggest that older Chinese Internet users perceived significantly less loneliness compared with their age peers who were non-Internet users. Zhang et al. investigated the role of information and communication technologies in supporting antiretroviral therapy (ART)-related knowledge seeking among older Chinese with HIV. Their cross-sectional survey data were collected from 2012 to 2013 in Guangxi, China. The results suggest that less than 5% of the participants sought HIV-related information via computers. Patients less knowledgeable about ART were more likely than those more knowledgeable to consult medical professionals about the disease via cell phones. Shiroma et al. report findings of a systematic literature review conducted in spring 2019 that examined Asian ethnic minority older adults’ preferences for end-of-Life (EOL) information seeking and decision making. The results suggest Asian ethnic minority older adults are understudied in the literature on EOL information and decision making, especially in terms of their unique cultural contexts. Du et al. examined how health information obtained from different types of social networks affect osteoporosis self-management behaviors among older White and Asian women.


Author(s):  
Juling Ding ◽  
Zhongjian Le ◽  
Ping Zhou ◽  
Gensheng Wang ◽  
Wei Shu
Keyword(s):  

Author(s):  
Anastasiia Zerkal ◽  
◽  
Viktoriia Holomb ◽  

The article considers the peculiarities of the formation of marketing communication strategies of the enterprise in terms of digitalization of the economy. The main directions of mass media in the twentieth century are determined and the delimitation of modern social media is presented. The conditions of compliance of the website have been determined so that it can be considered as a part of web 2.0: the ability to independently contribute to the content of the site; User control of your own information and website design -interactive and useful. The influence of digital and mobile technologies on the peculiarities of users' communication, as well as their attitude to the interactivity of social networks is proved. The potential of social networks to support their brands, increase the customer base and promote goods and services of enterprises has been identified. It is determined that due to its popularity, social networking sites have had a significant impact on ways of social communication and as a result have changed the sales channels of enterprises. It is estimated that the number of people using social networks is growing very fast, and at the time of writing, more than 2.62 billion people are using social networking sites. The largest social networks were analyzed: Facebook, Pinterest, Twitter, LinkedIn, Instagram. Their features and advantages for both users and professional marketers of enterprises are determined. It is estimated that in 2021, 71% of the total number of Internet users were users of social networks, and this percentage is projected to increase. The most popular activity among Internet users is social networking, and it has a high level of user engagement, which has a positive impact on the sales of businesses that work with digital marketing tools. The ease and low cost of Internet marketing compared to conventional advertising has proven that businesses in all sectors of the economy can more effectively reach their target audience, and social networks help influence other potential customers, and allow businesses to get useful feedback on their product or service. Ultimately, this leads to improved products / services and customer engagement, ie improves the company's marketing communication strategies in today's digital economy.


Author(s):  
Serhii Puhach

The intensive development of new information and communication technologies (ICT) has led to major changes in society. The widespread use of smartphones and mobile communications has allowed today to create new programs and services to improve human life. This development changes the established habits of human communication, the relationship between society and the environment. A social networking service (SNS) is a service (on a website or through a mobile application) that allows users to share a personal profile and establish contacts with other users. Social networking services affect the territorial organization of society and can be used for the development of both settlements and entire territories to make their development more sustainable and balanced. The study of social networking services is currently on the rise. The joint efforts of many sciences (sociology, psychology, geography, mathematics, statistics, computer science, etc.) are needed to understand the subject essence of the phenomenon and to analyze data. Approaches to the study of social networking services can be divided into three large groups: 1) in terms of human relations and relationships; 2) in terms of content distributed on the network; 3) in terms of spatial aspects of the functioning of the social network. In Ukraine, there are no detailed studies of the spatial aspects of the spread of social networking services at the local level. In the Ternopil region, there is a pattern of concentration of the majority of Facebook and Instagram users in the largest cities, namely Ternopil, Chortkiv, Berezhany, Kremenets. Buchach, Borshchiv, Zalishchyky, Terebovlya, and Shumsk districts stand out among the districts by the number of users. An important indicator that characterizes the spread of social networking services is the penetration rate of the social network, which is calculated as the ratio of the number of users in a certain territory to the population living in it. Cities of regional subordination differ in terms of the penetration rate of SNS. The highest values were observed in Chortkiv, Ternopil, Kremenets cities. The penetration rate of social networking services in the administrative districts of Ternopil region is much lower. A relatively high rate (over 30%) was recorded in Buchach, Berezhany and Shumsk districts. Extremely low penetration rate (less than 5%) is in Zbarazh, Chortkiv, Zboriv districts which are adjacent to the cities of regional subordination. The social networking service Instagram is inferior to Facebook in level of development, and its main users are mainly young people. However, in the territories where the rate of Facebook penetration is the lowest in the region (Ternopil, Zbarazh, Chortkiv, Zboriv districts), the predominance of Instagram is noted. Thus, the main patterns of spatial distribution of SNS’ Facebook and Instagram in Ternopil region are: concentration of users in the largest cities, especially in the regional center Ternopil City (half of Facebook and Instagram users in the region); the number of users is proportional to the population in the territorial unit; small number of users and low penetration rate of the SNS’ in the administrative districts adjacent to the cities of regional subordination Ternopil and Chortkiv; among administrative districts, higher indicators of social network development are typical for northern and southern districts in comparison with central ones. Key words: social networking service (SNS), penetration rate of the SNS, Facebook, Instagram, Ternopil region.


2011 ◽  
Vol 279 (1732) ◽  
pp. 1327-1334 ◽  
Author(s):  
R. Kanai ◽  
B. Bahrami ◽  
R. Roylance ◽  
G. Rees

The increasing ubiquity of web-based social networking services is a striking feature of modern human society. The degree to which individuals participate in these networks varies substantially for reasons that are unclear. Here, we show a biological basis for such variability by demonstrating that quantitative variation in the number of friends an individual declares on a web-based social networking service reliably predicted grey matter density in the right superior temporal sulcus, left middle temporal gyrus and entorhinal cortex. Such regions have been previously implicated in social perception and associative memory, respectively. We further show that variability in the size of such online friendship networks was significantly correlated with the size of more intimate real-world social groups. However, the brain regions we identified were specifically associated with online social network size, whereas the grey matter density of the amygdala was correlated both with online and real-world social network sizes. Taken together, our findings demonstrate that the size of an individual's online social network is closely linked to focal brain structure implicated in social cognition.


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