Behavior Of Social Media Users Research Articles

Causal Relationships Among Pollen Counts, Tweet Numbers, and Patient Numbers for Seasonal Allergic Rhinitis Surveillance: Retrospective Analysis.

BackgroundHealth-related social media data are increasingly used in disease-surveillance studies, which have demonstrated moderately high correlations between the number of social media posts and the number of patients. However, there is a need to understand the causal relationship between the behavior of social media users and the actual number of patients in order to increase the credibility of disease surveillance based on social media data.ObjectiveThis study aimed to clarify the causal relationships among pollen count, the posting behavior of social media users, and the number of patients with seasonal allergic rhinitis in the real world.MethodsThis analysis was conducted using datasets of pollen counts, tweet numbers, and numbers of patients with seasonal allergic rhinitis from Kanagawa Prefecture, Japan. We examined daily pollen counts for Japanese cedar (the major cause of seasonal allergic rhinitis in Japan) and hinoki cypress (which commonly complicates seasonal allergic rhinitis) from February 1 to May 31, 2017. The daily numbers of tweets that included the keyword “kafunshō” (or seasonal allergic rhinitis) were calculated between January 1 and May 31, 2017. Daily numbers of patients with seasonal allergic rhinitis from January 1 to May 31, 2017, were obtained from three healthcare institutes that participated in the study. The Granger causality test was used to examine the causal relationships among pollen count, tweet numbers, and the number of patients with seasonal allergic rhinitis from February to May 2017. To determine if time-variant factors affect these causal relationships, we analyzed the main seasonal allergic rhinitis phase (February to April) when Japanese cedar trees actively produce and release pollen.ResultsIncreases in pollen count were found to increase the number of tweets during the overall study period (P=.04), but not the main seasonal allergic rhinitis phase (P=.05). In contrast, increases in pollen count were found to increase patient numbers in both the study period (P=.04) and the main seasonal allergic rhinitis phase (P=.01). Increases in the number of tweets increased the patient numbers during the main seasonal allergic rhinitis phase (P=.02), but not the overall study period (P=.89). Patient numbers did not affect the number of tweets in both the overall study period (P=.24) and the main seasonal allergic rhinitis phase (P=.47).ConclusionsUnderstanding the causal relationships among pollen counts, tweet numbers, and numbers of patients with seasonal allergic rhinitis is an important step to increasing the credibility of surveillance systems that use social media data. Further in-depth studies are needed to identify the determinants of social media posts described in this exploratory analysis.

A study of characteristics of e-WoM affecting consumer's social media opinion behavior

Web-based social networking systems, for example, Facebook, Instagram and Twitter are changing the way word-of-mouth in electronic form (e-WoM) is spread and devoured in the online digital world. Because of increasing number of contemporary SNSs (social networking sites), marketers endeavor to utilize the power of digital mechanism in individual communication, through examination of characteristics of e-WoM that prompts opinion behavior of users of social media, which in turn influence buyers on social media sites. In this paper, it had been researched as to how various characteristics of e-WoM are affecting consumer opinion behaviour. This study has used exploratory research design and followed by model analysis. The collection of data was done by random sampling method from the respondents using structured questionnaire. An attempt is made to understand the relationship between the characteristics of e-WoM and three identified opinion behavior of the social media user. For both, the opinion behavior of the social media user and the e-WoM accordingly, this paper identifies various directly observed variables. Characteristics of e-WoM like privacy and dispersion were found to have significant impact on opinion giving behaviour of the users. Anonymity, privacy and deception too have significant impact on opinion giving behaviour of the users where as consumer engagement and dispersion have significant impact on pass along behaviour which are treated as manifest characteristics for e-WoM. Marketers require creating an e-WoM program by keeping relevant characteristics which influence more in mind to help embrace and execute digital media utilities to their business. The e-WoM program holds the capacity to stroke the opinion behavior of social media users.

ВЛИЯНИЕ ПОЛА И САМООЦЕНКИ ПОЛЬЗОВАТЕЛЕЙ СОЦИАЛЬНОЙ СЕТИ НА ИСПОЛЬЗОВАНИЕ ЭМОТИКОНОВ И ЭМОДЗИ В ПРОЦЕССЕ РЕЧЕВОЙ КОММУНИКАЦИИ

This article attempts to find the relationship between the socio-psychological characteristics and speech behavior of social media users. The comprehensive description of social media users is based on the models of integration of the social, behavioral, psychological and speech components of user profiles. In the article, sex of the informants and their level of self-esteem are considered as social and psychological para­meters; the graphic aspect of the collected text corpus (emoticons and emoji) is considered as a parameter of the users’ speech behavior. The research material includes 1) anonymous profile data of 299 participants of a psychological survey designed to establish the level of their self-esteem and 2) users’ texts (comments) in the social networking service VKontakte (https://vk.com). User-generated content was collected automatically using the social network API. The content consists of 19,179 user comments. Expert analysis of the graphical means (emoticons and emoji) was performed in the information system ‘Semograph’ (https://semograph.org). Based on emoticon and emoji libraries, collected speech material and existing theories of emotions, there was developed an emoticon and emoji classifier consisting of 15 ca­tegories. The classifier was used to annotate the content and subsequently generate the results of studying correspondences between graphic means (emoticons and emoji), self-esteem parameters and sex of infor­mants. In particular, the frequency of referring to the 15 emoticons and emoji categories was calculated, also the relationship between the use of certain categories and the self-esteem level in men and women was found. Furthermore, the influence of sex on the speech behavior of informants with different self-esteem le­vels was determined. It was found that the sex of informants has a more significant effect on the use of graphic means in social media communication than their psychological parameters.

A Study of Arabic Social Media Users—Posting Behavior and Author’s Gender Prediction

Social media opens up numerous possibilities to study human interaction and collective behavior in an unprecedented scale. It opened a whole new venue for research under the name “social computing”. Researchers are interested in profiling individuals (e.g., gender, age group), groups, community, and networking. We are interested in studying the collective behavior of Arabic social media users. Most studies covering Arabic social media has focused on the sentiment analysis of, say tweets. This study, however, looks into who and when users interact with the Arabic social media. Specifically, there are two objectives of this work. First, studying the demographic posting behavior of social media users from two different perspectives: gender and educational level. Second, author profiling. Identifying author’s gender of a social media post. We use Saudi Arabia, a very prolific country when it comes to social media in general, as a backdrop for this study. The results in this study are based on mining huge amount of metadata of a popular local social media forum covering the period 2011–14 inclusive. The extracted features (normalized list of k highest scoring words, and likewise for stems) from the posts were used to train classifiers to identify the author’s gender. We used two different classifiers, Support Vector Machine (SVM) with linear kernel and 1-NN (1-nearest neighbor), and experimented with different sizes for the list of features. When the number of features (size of the features vector) is small (≤ 50) both classifiers perform equally well in identifying the author’s gender, but we risk overfitting the data. The classifiers achieved their best result when using 100 features. The 1-NN classifier delivered a better performance, achieving a balanced accuracy of 93.16% vs 87.33% for the SVM in predicting the author’s gender. And for a larger set of features, SVM delivered a better performance and more stable behavior than 1-NN, but still nowhere close to its best performance. We used t test to confirm our assessment that the difference between the performance of both classifiers is statistically significant. Based on that, we recommend using 100 features, and we get our best result using 1-NN with a balanced accuracy of 93.16%.

E-Health: Attitude and Health Seeking Behavior of Social Media Users

E-Health: Attitude and Health Seeking Behavior of Social Media Users

Using social media for innovation – market segmentation of family firms

PurposeThe purpose of this study is to understand the strategy adopted by family firms in using social media for their business. Based on the social media usage, this paper attempts to segment family firms. To do so, a reactive – proactive – innovative (RPI) scale was developed for the study. Then, the family firms were categorised as reactive, proactive or innovative social media users. Further, based on the scale developed, clusters were created. Family firms were placed into different clusters based on the strategy that they had for using social media platforms for their business.Design/methodology/approachA pilot sample of 50 family firms and a main study of 256 Indian family firm entrepreneurs were surveyed through self-administered questionnaires. Factor analysis reduced the 12 scale-based questions to three distinct factors. Confirmatory factor analysis was then conducted on the main sample to confirm the constructs identified using exploratory factor analysis. Cluster analysis was used to build clusters of entrepreneurs who use social media as part of their digital marketing strategy.FindingsFindings reveal that the Indian family firm market is largely divided into four main segments. These segments represent distinct behaviours with respect to the use of social media. The four segments of family firm entrepreneurs were named as high rollers, ignorant inhabitants, trend-setters, combative crowd based on their social media usage behaviour. These clusters give deep insights into the strategic usage of social media by family firms.Research limitations/implicationsThe limitation of this study is that entrepreneurs from all Indian states were not considered in the sample because of cost implications. This research study has only created the segmentation of the family firms as reactive, proactive or innovative social media users and also has created the clusters as high rollers, ignorant inhabitants, trend-setters and combative crowd. Also, the reasons for their behaviour and root cause for the strategic usage have not been studied.Practical implicationsThis study reflects on current practices of family firms with respect to usage of social media and groups them into large identifiable clusters. Equipped with the findings from this study, the RPI scale developed for the study and the clusters created, entrepreneurs can now move towards better use of social media for innovation.Originality/valueAlthough past studies have advocated the use of social media to spur innovation in firms, this study segments the current market based on their practices. It allows readers to gauge the proportion of family firms using social media for innovation and paves the way for a change in behaviour amongst these firms.

Creating and Utilizing UGC Through Social Media in Trip Planning

This study aims to understand the behavior of social media users in creating and utilizing User Generated Content (UGC) in trip planning (before, during, and after the trip), and to inform which social media that mostly used by users. Through understanding the behavior of social media users in creating and utilizing UGC, this research is expected to contribute to the tourism organization in formulating promotion strategies in social media effectively. A survey is conducted to collect research data from 180 of communication students. This research found that Instagram (used by 96.7% of respondent) and Kaskus (used by 6.7% of respondent) have significant influence towards users in utilizing and creating the UGC in trip planning.

When and how does learning satisfy? Working collaboratively online with a clear purpose

Social-media platforms have become increasingly popular and important in daily life, and their use may affect students' learning satisfaction. The aim of this study was to determine whether social media enhance or detract from students' learning satisfaction by analysing the relationships between learners' social media usage behaviour, purpose in using social media, collaborative learning, and learning satisfaction. The research question was as follows: do social media enhance students' learning satisfaction? A questionnaire survey was administered to 204 university students. Social media usage behaviour (β = .128, p < .05) and academic purpose (β = .667, p < .001) were found to be directly, significantly, and positively related to collaborative learning (β = .763, p < .001), which in turn had a significant and direct positive effect on students' learning satisfaction (R2 = .582). The roles of social-media behaviour, purpose in using social media, and collaborative learning towards satisfaction were discussed.

Mapping of Airline Destinations According to Share Behavior in Social Media Using Multi-Dimensional Scale

With digital media becoming an important position in mass communication, information is shared and spread to those who use this media. Twitter in digital media is one of the most popular social media platforms that has come up with the combination of social network sites and blogs, with millions of members and the ability to share and spread information quickly. Sharing of information via electronic word of mouth (e-WOM) is one of the important issues that attract the attention of marketers. In this respect, this behavior of social media users is very important in sharing information by favorite or share of any posts on Twitter, as it is displayed by other users on their friends lists. This study aims to find out the location of each destination according to the share and reasons for reccommendation of users by looking at the destinations that are shared by Turkish Airlines (THY) on its official Twitter account in 2016. The study will reveal how city based destinations are in relation to others and the tendency of Turks to other destinations to be seen in concrete terms. By using multidimensional scaling analysis, the locations of destinations according to favorite and share statistics can be displayed in two dimensional space.

Comparison of airline destinations in terms of online consumer behaviours using multi dimentional scale analysis

With digital media becoming an important position in mass communication, information is shared and spread to those who use this media. Twitter in digital media is one of the most popular social media platforms that has come up with the combination of social network sites and blogs, with millions of members and the ability to share and spread information quickly. Sharing of information via electronic word of mouth (e-WOM) is one of the important issues that attract the attention of marketers. In this respect, this behavior of social media users is very important in sharing information by sharing, retweeting or liking of any posts on Twitter, as it is displayed by other users on their friends list. This study aims to find out the location of each destination according to the share, retweet, likes and reasons for reccommendation of users by looking at the destinations that are shared by Turkish Airlines (THY) on Twitter in 2016. The study will reveal how our country is in relation to other destinations and the tendency of Turks to other destinations to be seen in concrete terms. By using multidimensional scaling analysis, the locations of Turkey and other destinations can be displayed and evaluated in two dimensional space.

PERILAKU PENGGUNA DAN INFORMASI HOAX DI MEDIA SOSIAL

User behavior in sosial media and hoax information are an interesting phenomenon today. Social media is the most effective medium in Hoax's acceptance and dissemination of information. Various backgrounds of user behavior becomes one of the factors that make it easier for them to disseminate information without going through the verification process. Research method uses a qualitative descriptive method with research object of civitas academic environment of President University. The results show the behavior of social media users in responding Hoax information is quite diverse with a variety of user backgrounds. Users understand the Hoax information and impacts that arise after disseminating the information. The main reason the users spread the information Hoax is to influence the opinions/ attitudes of others. The other reason is to become a viral Social media users also understand that Hoax information can divide the nation. To inhibit the dissemination of hoax information, the role of government and parents is needed as well as the literacy/education of social media usage so that user behavior will be wise in responding to all information received. https://doi.org/10.26905/jmdk.v5i1.1342

Perilaku Pengguna Media Sosial beserta Implikasinya Ditinjau dari Perspektif Psikologi Sosial Terapan

Social media becomes a new tool for many areas to perform functions and works, such as political campaign media, advertising, and teaching. However, the use of social media nowadays also raises excessive effects which could be serious problems if it was not overcame as soon as possible. There are some social media usage behaviors that should be observed, such as selfie, cyber bullying, online shopping, user-personalization, and shared- culture. Through the study of social psychology, it is expected that readers have more comprehensive perspective in looking at the phenomenon of social media hegemony as part of contemporary social reality.

Discovery of repost patterns by topic analysis in enterprise social networking

PurposeAn increasing number of users are inspired by enterprises to repost social media messages, which greatly contributes to the dissemination of such messages in an online social network. The purpose of this paper is to discover the repost patterns of users regarding enterprise social media messages to help enterprises improve information management abilities for social media.Design/methodology/approachThis paper proposes a novel method to discover the repost patterns of users in enterprise social networking (ESN) at the macro-level through topic analysis. Specifically, it proposes the message-diversity metric to measure the latent topic diversity degree of the social media messages. Through this technique, the paper analyzes the message-diversity characteristics of the enterprise social media messages and then explores the repost patterns of users.FindingsThe experimental results show that a high repost rate is more prominent for the messages with diverse latent topics, where message-diversity is as high as 0.5.Practical implicationsThe findings have great potential in several management areas, such as employing social media marketing, predicting popular messages, helping enterprises strengthen their online presence, and gathering more potential customers.Originality/valueThis study explores how the repost patterns of users in ESN can be determined through general macro-level behavior of users instead of their micro-level processes. The patterns can also lead to a deeper understanding of which contents can drive people to diffuse information. This study gives an important insight into the information behavior of social media users for enterprise management researchers.

Private club members’ perceptions of social media

PurposePrivate club members belong to an organization where people with common interests, experiences, backgrounds and professions meet for social and recreational purposes. This study aims to examine the relationships among private club members’ perceptions of social media regarding perceived ease of use, perceived usefulness, perceived enjoyment, attitude toward social media involvement and behavioral intention toward social media usage.Design/methodology/approachAn online survey was conducted among private club members across the USA (n = 571). The data were analyzed using structural equation modeling.FindingsThe findings of this study center on the perceptions of club members and their beliefs and attitudes associated with their social media usage behavior. This study extends the social media literature by supporting previous studies that suggest a causal flow from perceived ease of use to intrinsic and extrinsic motivations (perceived usefulness, perceived enjoyment) based on a motivational model.Research limitations/implicationsThis study is meaningful for revealing the perceptions of private club members and their beliefs and attitudes associated with their social media usage behavior. It is untested whether this study’s model applies to other hospitality businesses. Future research could examine other segments and add other variables such as perceived security and trust.Practical implicationsThis study can provide private club managers, and the members of the clubs that they lead, with a better understanding of online social media.Originality/valueThis study is one of a few empirical online social media studies in the area of the private club industry. This study seeks to provide baselines regarding social media perceptions and usage in the hospitality literature by providing a comprehensive model.

Not all emotions are created equal: Expressive behavior of the networked public on China's social media site

This study attempts to investigate the online expressive behavior of social media users in China. Specifically, we combine machine learning-based textual analysis with social network analysis to examine the structure and content of the discussion network which formed around the political aspects of food safety issues on China's Twitter-like Weibo. The findings suggest that Weibo-mediated communication space does not serve as an effective forum for deliberative discussion because people of like mind tend to cluster and the factor of emotion predominates. Further statistical analyses of a hand-coded sample show that emotional discussions influence people more than cognitive discussions, with distinct emotions (e.g., anger, fear and sadness) having different effects. A poster's status is also found to matter. We contend that this kind of online civic talk underlines an expressive form of rationality that transcends the dominant bipolar instrumental-communicative dimension for understanding the use of social media in online political discussion.

The Managers Social Media Usage Behavior: An Application of the Theory of Planned Behavior

Given the widespread popularity of social media, such as Facebook and Twitter, social media is considered as a core business communication tool like the mobile phone and email are today. Hence, it is time to be aware of the importance of its impact at work, and how to use it effectively in order to develop the organization and promote business performance. Most of the researches conducted on using social media focused primarily on the individuals’ motivations and the organizations’ benefits. In fact, minimal amount of research has been conducted regarding the managers’ behavior towards using social media in their internal communication. Therefore, this research applied the theory of planned behavior (TPB) to identify and examine the factors that promote or discourage the behavior of managers regarding the usage of social media in the internal organizational context. The theoretical model was validated in a single cross-sectional empirical study of 204 participants. The data was analyzed using structural equation modeling to test the five hypotheses derived from the TPB on the sector level. Of the 5 hypotheses, only 4 were supported. The results add further evidence that the TPB can be applied in the field of organizational research in order to understand the factors that influence and determine the managers’ social media usage behavior.

Marketer-Generated Content Sharing Among Social Broadcasting Users: Effects of Intrinsic Motivations, Social Capital and the Moderating Role of Prevention Focus

Social networking services provide individuals with an easy approach for exchanging messages with others based on interpersonal relationships. However, why individuals spread marketer-generated content (MGC) in their online social circles remains unclear. Therefore, we develop a theoretical model to examine how social capital, intrinsic motivations, personal perceptions, past behavior, and personal traits influence MGC sharing behavior of social media users in micro-blogging context. Data collected from 319 social networking users support the proposed model. The results from partial least squares analyses show that enjoyment, perceived control, and outcome expectations are significant indicators of individual’s MGC sharing intention in the social broadcasting environment. Results also suggest that social capital, users’ intention, and past behavior positively influence the MGC sharing behavior of users. Moreover, individual prevention pride exhibits a significant interaction effect on the relationships between users’ MGC sharing and its antecedents. Implications for research and practice are discussed.

Determinants of Online Buying Behavior of Social Media Users in Saudi Arabia: An Exploratory Study

The exponential growth and proliferation of digital media technologies has revolutionized the global marketplace by giving rise to such paradigms as E-Commerce (EC). The study of numerous factors that support or inhibit online buying has received considerable attention by researchers. In this paper, we primarily focus on various factors that affect online buying within the context of the Kingdom of Saudi Arabia (KSA). We also discuss some theoretical approaches that are frequently used for defining, classifying, and explaining the e-consumer behaviour. Based on a sample of 990 Social Media users, the paper empirically examines the factors affecting the online buying focusing on the social media users. We also propose an empirical model for scientifically testing the significance of those factors and developing a model on online buying behaviour in the context of Saudi Arabia that may serve as a pilot for further examinations across the Arab world. The study is important because EC is expected to foster economic growth, productivity, and competitiveness of the firms in the country. Further, the research has scholarly importance for researchers interested in social sciences and management areas.

Influence in Microblogs: Impact of User Behavior on Diffusion and Engagement

Feature-rich social media can reveal many facets of individual user behavior; yet it is difficult to model such behavior due to both the noise and the overwhelming volume and heterogeneity in the data. In this paper, we address these challenges by building a model of user behavior in social media to understand the impact of users' actions on key influence outcomes. We specify models, inspired by social learning theory, that examine the outcome measures of followership (audience), diffusion (reach) and conversations (engagement) as functions of individual actions taken by a focal user within the medium. Our unique panel dataset is prepared by capturing and mining a snowball network of several thousand Twitter users and their activities over an extended period of time.Our results confirm that users' choices about specific actions can indeed positively affect performance on the above outcome measures; and establish a significant role for reciprocity within each outcome. We report several nuances of individual user behavior that may inform managers tasked with designing and executing social media strategies for firms. We find that creating fresh content of specific types as well as engaging in conversations are most effective in improving diffusion as well as leading to conversations. Interestingly, diffusing messages of other users in a focal user's reciprocal network helps with the focal user's own diffusion and conversations; whereas doing so for users outside the reciprocal network tends to hurt own diffusion and conversations.

Predictability of User Behavior in Social Media: Bottom-Up v Top-Down Modeling

There is a large amount of interest in understanding users of social media in order to predict their behavior in this space. Despite this interest, user predictability in social media is not well-understood. To examine this question, we consider a network of fifteen thousand users on Twitter over a seven week period. We apply two contrasting modeling paradigms: computational mechanics and echo state networks. Both methods attempt to model the behavior of users on the basis of their past behavior. We demonstrate that the behavior of users on Twitter can be well-modeled as processes with self-feedback. We find that the two modeling approaches perform very similarly for most users, but that they differ in performance on a small subset of the users. By exploring the properties of these performance-differentiated users, we highlight the challenges faced in applying predictive models to dynamic social data.