Search results
1 – 10 of 242Ying-Feng Kuo, Jian-Ren Hou and Yun-Hsi Hsieh
Netizens refer to citizens of the internet, and code-switching refers to the use of more than one language, style or form of expression to communicate. This study explores the…
Abstract
Purpose
Netizens refer to citizens of the internet, and code-switching refers to the use of more than one language, style or form of expression to communicate. This study explores the advertising communication effectiveness of using netizen language code-switching in Facebook ads. Moreover, if a brand is with negative brand images, using positive brand images as a control group, this study investigates not only the advertising communication effectiveness of netizen language code-switching but also its effectiveness of remedying the negative brand images.
Design/methodology/approach
Online experiments were conducted, and data were analyzed using independent sample t-test, MANOVA and ANOVA.
Findings
The results indicate that netizen language code-switching can enhance advertising communication effectiveness in Facebook ads. Furthermore, under a negative brand image, netizen language code-switching has significant effects on improving Facebook advertising communication effectiveness.
Originality/value
This study takes netizens as the research subjects to explore the advertising communication effectiveness of netizen language code-switching in Facebook ads. This study provides further insight into the effect of netizens' culture on Facebook advertising and enriches the existing literature on social media advertising, as well as expanding the application of code-switching. The results of this study provide enterprises a new perspective on the copywriting content design of Facebook ads.
Details
Keywords
Yuning Zhao, Xinxue Zhou and Tianmei Wang
Following Hovland’s persuasion theory, this paper aims to develop a conceptual model and analyzes characteristics of online political deliberation behavior from three aspects…
Abstract
Purpose
Following Hovland’s persuasion theory, this paper aims to develop a conceptual model and analyzes characteristics of online political deliberation behavior from three aspects (i.e. information, situation and manager). Based on the whole interactive process of online political deliberation, this paper aims to reveal the key points that affect the response effect of the government from the persuasive perspective of online political consultation.
Design/methodology/approach
Based on more than 40,000 netizens’ posts and government responses from 2011 to the first half of 2019 of the Chinese political platform, this paper used the text analysis and machine learning methods to extract measurement variables of online political deliberation characteristics and the econometrics analysis method to conduct empirical research.
Findings
The results showed that the textual information, political environment and identity of the political objects affect the effectiveness of government response. Furthermore, for different position categories of political officials, the length of political texts, topic categories and emotional tendencies have different effects on the response effectiveness. Additionally, the effect of political time on the effectiveness of response differs.
Originality/value
The findings will help ascertain the characteristics of online political deliberation behavior that affect how effective government response is and provide a theoretical basis for why the public should express their political concerns.
Details
Keywords
Jiakun Wang and Yun Li
Under the new media environment, while enjoying the convenience brought by the propagation of public opinion information (referred to as public opinion), learning the evolution…
Abstract
Purpose
Under the new media environment, while enjoying the convenience brought by the propagation of public opinion information (referred to as public opinion), learning the evolution process of public opinion and strengthening the governance of the spreading of public opinion are of great significance to promoting economic development and maintaining social stability as well as effectively resisting the negative impact of its propagation.
Design/methodology/approach
Thinking about the results of empirical research and bibliometric analysis, this paper focused on introducing key factors such as information content, social strengthening effects, etc., from both internal and external levels, dynamically designed public opinion spreading rules and netizens' state transition probability. Subsequently, simulation experiments were conducted to discuss the spreading law of public opinion in two types of online social networks and to identify the key factors which influencing its evolution process. Based on the experimental results, the governance strategies for the propagation of negative public opinion were proposed finally.
Findings
The results show that compared with other factors, the propagation of public opinion depends more on the attributes of the information content itself. For the propagation of negative public opinion, on the one hand, the regulators should adopt flexible guidance strategy to establish a public opinion supervision mechanism and autonomous system with universal participation. On the other hand, they still need to adopt rigid governance strategy, focusing on the governance timing and netizens with higher network status to forestall the wide-diffusion of public opinion.
Practical implications
The research conclusions put forward the enlightenment for the governance of public opinion in management practice, and also provided decision-making reference for the regulators to reasonably respond to the propagation of public opinion.
Originality/value
Our research proposed a research framework for the discussion of public opinion propagation process and had important practical guiding significance for the governance of public opinion propagation.
Details
Keywords
Jinghuan Zhang, Shan Wang, Wenfeng Zheng and Lei Wang
By drawing on the research paradigm of collective action that occurs in physical space, the present study aims to explore the antecedent predictors of network social mobilization…
Abstract
Purpose
By drawing on the research paradigm of collective action that occurs in physical space, the present study aims to explore the antecedent predictors of network social mobilization – feeling of injustice – and discuss the emotional mechanism of this prediction: mediating effect of anger and resentment.
Design/methodology/approach
Micro-blog postings about network social mobilization were collected to develop the dictionary of codes of fairness, anger and resentment. Then, according to the dictionary, postings on Sina Weibo were coded and analyzed.
Findings
The feeling of injustice predicted network social mobilization directly. The predictive value was 27% and 33%, respectively during two analyses. The feeling of injustice also predicted social mobilization indirectly via anger and resentment. In other words, anger and resentment account for the active mechanism in which the feeling of injustice predicts network social mobilization. Mediating effect value was 29.63% and 33.33% respectively.
Research limitations/implications
This study is our first exploration to use python language to collect data from human natural language pointing on micro-blog, a large number of comments of netizen about certain topic were crawled, but a small portion of the comments could be coded into analyzable data, which results in a doubt of the reliability of the study. Therefore, we should put the established model under further testing.
Practical implications
In the cyberspace, this study confirms the mechanism of network social mobilization, expands and enriches the research on social mobilization and deepens the understanding of social mobilization.
Social implications
This study provides an empirical evidence to understand the network social mobilization, and it gives us the clue to control the process of network social mobilization.
Originality/value
This study uses the Python language to write Web crawlers to obtain microblog data and analyze the microblog content for word segmentation and matching thesaurus. It has certain innovation.
Details
Keywords
This study argues that online user comments on social media platforms provide feedback and evaluation functions. These functions can provide services for the relevant departments…
Abstract
Purpose
This study argues that online user comments on social media platforms provide feedback and evaluation functions. These functions can provide services for the relevant departments of organizations or institutions to formulate corresponding public opinion response strategies.
Design/methodology/approach
This study considers Chinese universities’ public opinion events on the Weibo platform as the research object. It collects online comments on Chinese universities’ network public opinion governance strategy texts on Weibo, constructs the sentiment index based on sentiment analysis and evaluates the effectiveness of the network public opinion governance strategy adopted by university officials.
Findings
This study found the following: First, a complete information release process can effectively improve the effect of public opinion governance strategies. Second, the effect of network public opinion governance strategies was significantly influenced by the type of public opinion event. Finally, the effect of public opinion governance strategies is closely related to the severity of punishment for the subjects involved.
Research limitations/implications
The theoretical contribution of this study lies in the application of image repair theory and strategies in the field of network public opinion governance, which further broadens the scope of the application of image repair theory and strategies.
Originality/value
This study expands online user comment research to network public opinion governance and provides a quantitative method for evaluating the effect of governance strategies.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2022-0269
Details
Keywords
Qingqing Li, Ziming Zeng, Shouqiang Sun, Chen Cheng and Yingqi Zeng
The paper aims to construct a spatiotemporal situational awareness framework to sense the evolutionary situation of public opinion in social media, thus assisting relevant…
Abstract
Purpose
The paper aims to construct a spatiotemporal situational awareness framework to sense the evolutionary situation of public opinion in social media, thus assisting relevant departments in formulating public opinion control measures for specific time and space contexts.
Design/methodology/approach
The spatiotemporal situational awareness framework comprises situational element extraction, situational understanding and situational projection. In situational element extraction, the data on the COVID-19 vaccine, including spatiotemporal tags and text contents, is extracted. In situational understanding, the bidirectional encoder representation from transformers – latent dirichlet allocation (BERT-LDA) and bidirectional encoder representation from transformers – bidirectional long short-term memory (BERT-BiLSTM) are used to discover the topics and emotional labels hidden in opinion texts. In situational projection, the situational evolution characteristics and patterns of online public opinion are uncovered from the perspective of time and space through multiple visualisation techniques.
Findings
From the temporal perspective, the evolution of online public opinion is closely related to the developmental dynamics of offline events. In comparison, public views and attitudes are more complex and diversified during the outbreak and diffusion periods. From the spatial perspective, the netizens in hotspot areas with higher discussion volume are more rational and prefer to track the whole process of event development, while the ones in coldspot areas with less discussion volume pay more attention to the expression of personal emotions. From the perspective of intertwined spatiotemporal, there are differences in the focus of attention and emotional state of netizens in different regions and time stages, caused by the specific situations they are in.
Originality/value
The situational awareness framework can shed light on the dynamic evolution of online public opinion from a multidimensional perspective, including temporal, spatial and spatiotemporal perspectives. It enables decision-makers to grasp the psychology and behavioural patterns of the public in different regions and time stages and provide targeted public opinion guidance measures and offline event governance strategies.
Details
Keywords
M. Kabir Hassan, Fahmi Ali Hudaefi and Rezzy Eko Caraka
This paper aims to explore netizen’s opinions on cryptocurrency under the lens of emotion theory and lexicon sentiments analysis via machine learning.
Abstract
Purpose
This paper aims to explore netizen’s opinions on cryptocurrency under the lens of emotion theory and lexicon sentiments analysis via machine learning.
Design/methodology/approach
An automated Web-scrapping via RStudio is performed to collect the data of 15,000 tweets on cryptocurrency. Sentiment lexicon analysis is done via machine learning to evaluate the emotion score of the sample. The types of emotion tested are anger, anticipation, disgust, fear, joy, sadness, surprise, trust and the two primary sentiments, i.e. negative and positive.
Findings
The supervised machine learning discovers a total score of 53,077 sentiments from the sampled 15,000 tweets. This score is from the artificial intelligence evaluation of eight emotions, i.e. anger (2%), anticipation (18%), disgust (1%), fear (3%), joy (15%), sadness (3%), surprise (7%), trust (15%) and the two sentiments, i.e. negative (4%) and positive (33%). The result indicates that the sample primarily contains positive sentiments. This finding is theoretically significant to measure the emotion theory on the sampled tweets that can best explain the social implications of the cryptocurrency phenomenon.
Research limitations/implications
This work is limited to evaluate the sampled tweets’ sentiment scores to explain the social implication of cryptocurrency.
Practical implications
The finding is necessary to explain the recent phenomenon of cryptocurrency. The positive sentiment may describe the increase in investment in the decentralised finance market. Meanwhile, the anticipation emotion may illustrate the public’s reaction to the bubble prices of cryptocurrencies.
Social implications
Previous studies find that the social signals, e.g. word-of-mouth, netizens’ opinions, among others, affect the cryptocurrencies’ movement prices. This paper helps explain the social implications of such dynamic of pricing via sentiment analysis.
Originality/value
This study contributes to theoretically explain the implications of the cryptocurrency phenomenon under the emotion theory. Specifically, this study shows how supervised machine learning can measure the emotion theory from data tweets to explain the implications of cryptocurrencies.
Details
Keywords
Jitendra Yadav, Kuldeep Singh, Nripendra P. Rana and Denis Dennehy
Social media has played a pivotal role in polarizing views on Russia–Ukraine conflict. The effects of polarization in online interactions have been extensively studied in many…
Abstract
Purpose
Social media has played a pivotal role in polarizing views on Russia–Ukraine conflict. The effects of polarization in online interactions have been extensively studied in many contexts. This research aims to examine how multiple social media sources may act as an integrator of information and act as a platform for depolarizing behaviors.
Design/methodology/approach
This study analyzes the communications of 6,662 tweets related to the sanctions imposed on Russia by using textual analytics and predictive modeling.
Findings
The research findings reveal that the tweeting behavior of netizens was depolarized because of information from multiple social media sources. However, the influx of information from non-organizational sources such as trending topics and discussions has a depolarizing impact on the user’s pre-established attitude.
Research limitations/implications
For policymakers, conflict mediators and observers, and members of society in general, there is a need for (1) continuous and consistent communication throughout the crisis, (2) transparency in the information being communicated and (3) public awareness of the polarized and conflicting information being provided from multiple actors that may be biased in the claims being made about the conflict crisis.
Originality/value
While previous research has examined Russia–Ukraine conflict from a variety of perspectives, this is the first study to examine how social media might be used to reduce attitude polarization during times of conflict.
Details
Keywords
Xiaodong Li, Chuang Wang and Yanping Zhang
Due to customers' extensive avoidance behavior, social commerce may be less successful than anticipated. This study investigates the underlying mechanism and antecedents that…
Abstract
Purpose
Due to customers' extensive avoidance behavior, social commerce may be less successful than anticipated. This study investigates the underlying mechanism and antecedents that influence customers' avoidance of peer-generated advertisements.
Design/methodology/approach
Based on the general framework of avoidance behavior, we propose a theoretical model for the context of a mobile social network, with tie strength as the user-related factor and violation of shared language, advertisement relevance and information overload as contextual variables. Using survey data collected from 334 customers on WeChat, we empirically examine the research model and hypotheses.
Findings
Tie strength and advertisement relevance are negatively associated with avoidance behavior, whereas information overload and violation of shared language have significantly positive effects. Furthermore, tie strength weakens the negative relationship between violation of shared language and avoidance behavior but strengthens the positive relationship between advertisement relevance and avoidance behavior.
Originality/value
The findings extend understanding of advertisement avoidance behavior and can guide practitioners' improvement of advertising efficiency in mobile social networks.
Details
Keywords
Shixiong Wang and Yu Song
The purpose of this paper is to use Weibo as a window to examine the Chinese netizens’ online attitudes and responses to two sets of population policy: the Selective Two-Child…
Abstract
Purpose
The purpose of this paper is to use Weibo as a window to examine the Chinese netizens’ online attitudes and responses to two sets of population policy: the Selective Two-Child Policy (Phase 2) and the Universal Two-Child Policy. The population policy change from the rigid One-Child Policy to the Selective Two-Child Policy then to the Universal Two-Child Policy aroused great attention of the Chinese people.
Design/methodology/approach
This research uses the crawler technique to extract data on the Sina Weibo platform. Through opinion mining of Weibo posts on two sets of population policy, the Weibo users’ online opinions on the Two-Child Policy are analyzed from two perspectives: their attention intensity and sentiment tendency. The research also use the State Bureau of Statistics of China’s national population data between 2011 and 2016 to examine the Chinese people’s actual birth behaviors after implementing the two different sets of the Two-Child Policy.
Findings
The research findings indicate that the Selective Two-Child Policy (Phase 2) and the Universal Two-Child Policy are good examples of thematic public sphere of Weibo. Weibo posts on the two sets of the Two-Child Policy have undergone different opinion cycles. People from economically developed regions and populous regions have paid more attention to both sets of Two-Child Policy than their counterparts in the less developed and less populated regions. Men pay more attention to the Two-Child Policy than women do. Despite people’s huge attention to the new population policy, the population growth after the policy is not sustainable.
Research limitations/implications
The new population policy alone is difficult to boost China’s population within a short period of time. The Chinese Government must provide its people with enough incentives and supporting welfare to make the population growth happen.
Originality/value
These findings have important implications for understanding the dynamics of online opinion formation and changing population policy in China.
Details