scholarly journals The Linguistic Characteristics and Functions of Hashtags: #Is it a New Language?

2020 ◽  
Author(s):  
Iman Mahfouz
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Information Diffusion ◽  
Arabic Language ◽  
Syntactic Features ◽  
Linguistic Research ◽  
Linguistic Functions ◽  
Similarities And Differences ◽  
Everyday Communication

Defined as a form of tagging that allows social media users to embed metadata in their posts, hashtags initially served to categorize topics and make them searchable online. Originating first on Twitter in 2007, hashtags have spread to other platforms, such as Instagram, Facebook, and Youtube. In addition to functioning as topic markers, hashtags have developed more complex linguistic functions. The ubiquity of this feature in the online medium, which now occupies a significant portion of our everyday communication is thus worthy of investigation. Although this topic has been researched in different disciplines, such as information diffusion, marketing, as well as sociology and public opinion, hashtags have not yet received enough attention from linguistic research. Using a sample of hashtags from a corpus of Instagram posts by Egyptian and Arab participants, this research thus aims to examine the characteristics of hashtags from a linguistic perspective, with particular focus on hashtags in the Arabic language. The study primarily seeks to determine the morpho-syntactic features of these recently emerging linguistic items according to the taxonomy proposed by Caleffi (2015). It also explores the pragmatic functions of hashtags based on Zappavigna’s (2015) view of hashtags as technologically discursive tools. The analysis points out that most of the hashtags in the data serve the experiential function and come as suffixes. The findings reveal both similarities and differences between English and Arabic hashtags.

Methodological Problems of Using Arabic-Language Twitter as a Gauge for Arab Attitudes Toward Politics and Society

2020 ◽  
pp. 234779892097628
Author(s):  
Mujtaba Ali Isani
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Sentiment Analysis ◽  
General Public ◽  
Middle Eastern ◽  
Arabic Language ◽  
Measurement Bias ◽  
Comprehensive Review ◽  
Methodological Problems ◽  
Twitter Users

Public opinion research in the Middle Eastern context has seen a proliferation of data research that aims to track changes in the state of Arab attitudes. Yet, it remains unclear what is being measured and how representative the data is. This article aims to address this question by reviewing the extent to which and how the existing literature has addressed the issues of representativeness of Twitter communities and the validity of opinion measures derived from sentiment analysis in the Middle Eastern context. While some studies aim no further than to gauge the dynamics of Twitter debates, many others seek to generalize the larger public opinion trends. This raises questions about how representative Twitter users are of the general public, how asymmetric social media use is, and how participation routines vary. Furthermore, to what extent can sentiment analysis translate individual tweets into meaningful measures of expressed opinion, and how sensitive are means of aggregating opinions from sentiment analysis to variation in terms of tone and amount of text within and across individuals? Following a comprehensive review of existing research in the context of the Middle East, this article also aims to derive a clearer understanding of how collective Twitter opinion relates to public opinion and make some suggestions of ways to design sampling and coding procedures, as well as validation exercises to address measurement bias and error.

Analysis of Sentiment of Moving a National Capital with Feature Selection Naive Bayes Algorithm and Support Vector Machine

2020 ◽  
Vol 4 (3) ◽  
pp. 504-512
Author(s):  
Faried Zamachsari ◽  
Gabriel Vangeran Saragih ◽  
Susafa'ati ◽  
Windu Gata
Keyword(s):  
Social Media ◽  
Support Vector Machine ◽  
Feature Selection ◽  
Public Opinion ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Capital City ◽  
Support Vector ◽  
National Capital ◽  
Bayes Algorithm

The decision to move Indonesia's capital city to East Kalimantan received mixed responses on social media. When the poverty rate is still high and the country's finances are difficult to be a factor in disapproval of the relocation of the national capital. Twitter as one of the popular social media, is used by the public to express these opinions. How is the tendency of community responses related to the move of the National Capital and how to do public opinion sentiment analysis related to the move of the National Capital with Feature Selection Naive Bayes Algorithm and Support Vector Machine to get the highest accuracy value is the goal in this study. Sentiment analysis data will take from public opinion using Indonesian from Twitter social media tweets in a crawling manner. Search words used are #IbuKotaBaru and #PindahIbuKota. The stages of the research consisted of collecting data through social media Twitter, polarity, preprocessing consisting of the process of transform case, cleansing, tokenizing, filtering and stemming. The use of feature selection to increase the accuracy value will then enter the ratio that has been determined to be used by data testing and training. The next step is the comparison between the Support Vector Machine and Naive Bayes methods to determine which method is more accurate. In the data period above it was found 24.26% positive sentiment 75.74% negative sentiment related to the move of a new capital city. Accuracy results using Rapid Miner software, the best accuracy value of Naive Bayes with Feature Selection is at a ratio of 9:1 with an accuracy of 88.24% while the best accuracy results Support Vector Machine with Feature Selection is at a ratio of 5:5 with an accuracy of 78.77%.

Chinese Social Media Platforms and Microblogging in the Context of Public Diplomacy

Communicology ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 167-179
Author(s):  
E.S. Nadezhkina
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Public Diplomacy ◽  
User Generated Content ◽  
The Internet ◽  
Interactive Communication ◽  
Network Interaction ◽  
Social Media Platforms ◽  
The Right ◽  
Chinese Social Media

The term “digital public diplomacy” that appeared in the 21st century owes much to the emergence and development of the concept of Web 2.0 (interactive communication on the Internet). The principle of network interaction, in which the system becomes better with an increase in the number of users and the creation of user-generated content, made it possible to create social media platforms where news and entertainment content is created and moderated by the user. Such platforms have become an expression of the opinions of various groups of people in many countries of the world, including China. The Chinese segment of the Internet is “closed”, and many popular Western services are blocked in it. Studying the structure of Chinese social media platforms and microblogging, as well as analyzing targeted content is necessary to understand China’s public opinion, choose the right message channels and receive feedback for promoting the country’s public diplomacy. This paper reveals the main Chinese social media platforms and microblogging and provides the assessment of their popularity, as well as possibility of analyzing China’s public opinion based on “listening” to social media platforms and microblogging.

scholarly journals COVID-19 conspiracy theories

2021 ◽  
Vol 24 (2) ◽  
pp. 270-275 ◽  
Author(s):  
Karen M. Douglas
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Intergroup Relations ◽  
Group Processes ◽  
Negative Consequences ◽  
Conspiracy Theories ◽  
Open Questions ◽  
Potential Impact

Conspiracy theories started to appear on social media immediately after the first news about COVID-19. Is the virus a hoax? Is it a bioweapon designed in a Chinese laboratory? These conspiracy theories typically have an intergroup flavour, blaming one group for having some involvement in either manufacturing the virus or controlling public opinion about it. In this article, I will discuss why people are attracted to conspiracy theories in general, and why conspiracy theories seem to have flourished during the pandemic. I will discuss what the consequences of these conspiracy theories are for individuals, groups, and societies. I will then discuss some potential strategies for addressing the negative consequences of conspiracy theories. Finally, I will consider some open questions for research regarding COVID-19 conspiracy theories, in particular focusing on the potential impact of these conspiracy theories for group processes and intergroup relations.

Profiling the Users of High Influence on Social Media in the Context of Public Events

2021 ◽  
Vol 32 (2) ◽  
pp. 36-49
Author(s):  
Lu An ◽  
Junyang Hu ◽  
Manting Xu ◽  
Gang Li ◽  
Chuanming Yu
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Emergency Management ◽  
Emotional Support ◽  
Opinion Leader ◽  
Negative Effects ◽  
The Public ◽  
Public Events ◽  
Social Media Platforms ◽  
Influential Users

The highly influential users on social media platforms may lead the public opinion about public events and have positive or negative effects on the later evolution of events. Identifying highly influential users on social media is of great significance for the management of public opinion in the context of public events. In this study, the highly influential users of social media are divided into three types (i.e., topic initiator, opinion leader, and opinion reverser). A method of profiling highly influential users is proposed based on topic consistency and emotional support. The event of “Jiankui He Editing the Infants' Genes” was investigated. The three types of users were identified, and their opinion differences and dynamic evolution were revealed. The comprehensive profiles of highly influential users were constructed. The findings can help emergency management departments master the focus of attention and emotional attitudes of the key users and provide the method and data support for opinion management and decision-making of public events.

Rapid Perception of Public Opinion in Emergency Events through Social Media

2022 ◽  
Vol 23 (2) ◽  
Author(s):  
Yudi Chen ◽  
Yun Li ◽  
Zifu Wang ◽  
Alma Joanna Quintero ◽  
Chaowei Yang ◽  
...  
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Emergency Events

scholarly journals Verbal Arabic Mistakes of Ustadz in Conveying the Materials of Islamic Preaching/Kesalahan Ustaz dalam Bahasa Arab Verbal pada Penyampaian Materi Dakwah Islam

2021 ◽  
Vol 5 (1) ◽  
pp. 39
Author(s):  
Muhamad Agus Mushodiq ◽  
Muhammad Syaifullah ◽  
Dian Risky Amalia ◽  
Nailul Izzah ◽  
Bety Dwi Pratiwi
Keyword(s):  
Social Media ◽  
Qualitative Method ◽  
Language Skills ◽  
Arabic Language ◽  
Separate Analysis ◽  
Primary Language ◽  
Analysis Method ◽  
Descriptive Qualitative

This paper aims to reveal the mistakes of micro Arabic in the aspects of Ilm Saut (phonology), Sharaf (morphology), Nahw (Syntax), and 'Ilm Dalalah (Semantics) in preaching materials conveyed by ustadz and ustadzah included in the groups of "Ustadz Sunnah" and "Islam itu Indah". Arabic mistakes are often made by ustadz and ustadzah who often appear on social media. In general, an ustadz must have good Arabic language skills. The vast emergence of ustadz and ustadzah on social media is allegedly not accompanied by their qualified mastery of the primary language used in Islamic teaching sources and primary books, namely Arabic. Hence, the researchers used micro linguistic theories comprising the studies of phonology, morphology, syntax, and semantics therein. This study applied a descriptive-qualitative method. Researchers not only described the Arabic mistakes made by those of "Ustadz Sunnah” and "Islam itu Indah" but also provided corrections to such mistakes. In analyzing the data, the researchers used a separate analysis method. The findings demonstrated that those of "Ustaz Sunnah" and "Islam itu Indah” made mistakes in verbal Arabic at phonemic, morphemic, syntactic, and semantic levels.

scholarly journals The impact of credibility of influencers recommendations on social media on consumers behavior towards brands

2021 ◽  
Vol 54 (3-4) ◽  
pp. 181-196
Author(s):  
Piotr Kwiatek ◽  
Radoslav Baltezarević ◽  
Stavros Papakonstantinidis
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Virtual Environment ◽  
Word Of Mouth ◽  
Consumer Attitudes ◽  
Time Frame ◽  
Target Market ◽  
Online Environment ◽  
Purchasing Decisions ◽  
The Impact

Companies are becoming increasingly aware of the importance and opportunities provided by social media in order to communicate faster and more efficiently with their consumers. In order to convey the message about the value of their brands to their target market, organizations hire influential people who are considered to be the creators of public opinion in a virtual environment. Nowadays, social media are crowded with micro and macro influencers, or at least those who present themselves as such. Their main job is to represent and recommend brands to other users (their followers) and thus influence consumer attitudes about brands and possibly strengthen their purchasing decisions. Very often, influencers on social media are hired by companies to promote their brands for a fee. In order to have more control over their communication activities, companies provide them, in advance, with the content they want to be conveyed to consumers, but also the time frame when the message should be launched. In this way, organizations try to reduce the risk of turning electronic word-of-mouth (EWOM) communication into a negative one. In order for consumers to trust the recommendations of influencers on social media, these people need to have significant expertise in a certain area, charisma and respect from other users, so that their credibility affects the value of content and recommendations they place in the online environment. The aim of this paper is to present the attitudes of respondents who use social media websites about the impact of the credibility of influencers' recommendations on social media, and their opinion on whether and in what way their credibility influences consumer attitudes towards brands.

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