scholarly journals Social Media Analytics: Data Utilization of Social Media for Research

2019 ◽  
Vol 1 (2) ◽  
pp. 193-205
Author(s):  
Ria Andryani ◽  
Edi Surya Negara ◽  
Dendi Triadi

The amount of production data generated by social media opportunities that can be exploited by various parties, both government and private sectors to produce the information. Social media data can be used to know the behavior and public perception of the phenomenon or a particular event. To obtain and analyze social media data needed depth knowledge of Internet technology, social media, databases, data structures, information theory, data mining, machine learning, until the data and information visualization techniques. In this research, social media analysis on a particular topic and the development of prototype devices software used as a tool of social media data retrieval or retrieval of data applications. Social Media Analytics (SMA) aims to make the process of analysis and synthesis of social media data to produce information can be used by those in need. SMA process is done in three stages, namely: Capture, Understand and Present. This research is exploratorily focused on understanding the technology that became the basis of social media using various techniques exist and is already used in the study of social media analytic previously.

Author(s):  
Ibrahim Sabuncu ◽  
Mehmet Emin Aydin

Social media analytics appears as one of recently developing disciplines that helps understand public perception, reaction, and emerging developments. Particularly, pandemics are one of overwhelming phenomena that push public concerns and necessitate serious management. It turned to be a useful tool to understand the thoughts, concerns, needs, expectations of public and individuals, and supports public authorities to take measures for handling pandemics. It can also be used to predict the spread of the virus, spread parameters, and to estimate the number of cases in the future. In this chapter, recent literature on use of social media analytics in pandemic management is overviewed covering all relevant studies on various aspects of pandemic management. It also introduces social media data sources, software, and tools used in the studies, methodologies, and AI techniques including how the results of the analysis are used in pandemic management. Consequently, the chapter drives conclusions out of findings and results of relevant analysis.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Michael S. Lin ◽  
Yun Liang ◽  
Joanne X. Xue ◽  
Bing Pan ◽  
Ashley Schroeder

Purpose Recent tourism research has adopted social media analytics (SMA) to examine tourism destination image (TDI) and gain timely insights for marketing purposes. Comparing the methodologies of SMA and intercept surveys would provide a more in-depth understanding of both methodologies and a more holistic understanding of TDI than each method on their own. This study aims to investigate the unique merits and biases of SMA and a traditional visitor intercept survey. Design/methodology/approach This study collected and compared data for the same tourism destination from two sources: responses from a visitor intercept survey (n = 1,336) and Flickr social media photos and metadata (n = 11,775). Content analysis, machine learning and text analysis techniques were used to analyze and compare the destination image represented from both methods. Findings The results indicated that the survey data and social media data shared major similarities in the identified key image phrases. Social media data revealed more diverse and more specific aspects of the destination, whereas survey data provided more insights in specific local landmarks. Survey data also included additional subjective judgment and attachment towards the destination. Together, the data suggested that social media data should serve as an additional and complementary source of information to traditional survey data. Originality/value This study fills a research gap by comparing two methodologies in obtaining TDI: SMA and a traditional visitor intercept survey. Furthermore, within SMA, photo and metadata are compared to offer additional awareness of social media data’s underlying complexity. The results showed the limitations of text-based image questions in surveys. The findings provide meaningful insights for tourism marketers by having a more holistic understanding of TDI through multiple data sources.


2019 ◽  
Vol 10 (2) ◽  
pp. 57-70 ◽  
Author(s):  
Vikas Kumar ◽  
Pooja Nanda

With the amplification of social media platforms, the importance of social media analytics has exponentially increased for many brands and organizations across the world. Tracking and analyzing the social media data has been contributing as a success parameter for such organizations, however, the data is being poorly harnessed. Therefore, the ethical implications of social media analytics need to be identified and explored for both the organizations and targeted users of social media data. The present work is an exploratory study to identify the various techno-ethical concerns of social media engagement, as well as social media analytics. The impact of these concerns on the individuals, organizations, and society as a whole are discussed. Ethical engagement for the most common social media platforms has been outlined with a number of specific examples to understand the prominent techno-ethical concerns. Both the individual and organizational perspectives have been taken into account to identify the implications of social media analytics.


2021 ◽  
Author(s):  
Elizabeth Dubois ◽  
Anatoliy Gruzd ◽  
Jenna Jacobson

Journalists increasingly use social media data to infer and report public opinion by quoting social media posts, identifying trending topics, and reporting general sentiment. In contrast to traditional approaches of inferring public opinion, citizens are often unaware of how their publicly available social media data is being used and how public opinion is constructed using social media analytics. In this exploratory study based on a census-weighted online survey of Canadian adults (N=1,500), we examine citizens’ perceptions of journalistic use of social media data. We demonstrate that: (1) people find it more appropriate for journalists to use aggregate social media data rather than personally identifiable data; (2) people who use more social media are more likely to positively perceive journalistic use of social media data to infer public opinion; and (3) the frequency of political posting is positively related to acceptance of this emerging journalistic practice, which suggests some citizens want to be heard publicly on social media while others do not. We provide recommendations for journalists on the ethical use of social media data and social media platforms on opt-in functionality.


2021 ◽  
Author(s):  
Kashif Ali ◽  
Margaret Hamilton ◽  
Charles Thevathayan ◽  
Xiuzhen Zhang

Abstract Social media provides an infrastructure where users can share their data at an unprecedented speed without worrying about storage and processing. Social media data has grown exponentially and now there is major interest in extracting any useful information from the social media data to apply in various domains. Currently, there are various tools available to analyze the large amounts of social media data. However, these tools do not consider the diversity of the social media data, and treat social media as a uniform data source with similar features. Thus, these tools lack the flexibility to dynamically process and analyze the social media data according to its diverse features. In this paper, we develop a `Big Social Data as a Service' (BSDaaS) composition framework that extracts the data from various social media platforms, and transforms it into useful information. The framework provides a quality model to capture the dynamic features of social media data. In addition, our framework dynamically assesses the quality features of the social media data and composes appropriate services required for various information analyses. We present a social media based sentiment analysis system as a motivating scenario and conduct experiments using real-world datasets to show the efficiency of our approach.


2016 ◽  
Vol 28 (2) ◽  
pp. 1-12 ◽  
Author(s):  
Samuel Fosso Wamba ◽  
Shahriar Akter ◽  
Hyunjin Kang ◽  
Mithu Bhattacharya ◽  
Mohammed Upal

This article is intended to serve as a primer of social media analytics. The paper explores different dimensions of social media analytics by drawing on a review of the literature. Specifically, the paper sheds light on the definitional aspects, types of social media data and types of analytics to improve firm performance. The findings of the paper will help the reader to grasp the fundamentals of social media analytics.


2019 ◽  
Vol 40 (1) ◽  
pp. 28-34 ◽  
Author(s):  
Lisa Tam ◽  
Jeong-Nam Kim

Purpose In the midst of practitioners’ increasing use of social media analytics (SMA) in guiding public relations (PR) strategy, this paper aims to present the capabilities and limitations of these tools and offers suggestions on how to best use them to gain research-based insights. Design/methodology/approach This review assesses the capabilities and limitations of SMA tools based on industry reports and research articles on trends in PR and SMA. Findings The strengths of SMA tools lie in their capability to gather and aggregate a large quantity of real-time social media data, use algorithms to analyze the data and present the results in ways meaningful to organizations and understand networks of issues and publics. However, there are also challenges, including the increasing restricted access to social media data, the increased use of bots, skewing social conversations in the public sphere, the lack of capability to analyze certain types of data, such as visual data and the discrepancy between data collected on social media and through other methods. Originality/value This review suggests that PR professionals acknowledge the capabilities and limitations of SMA tools when using them to inform strategy.


2015 ◽  
Vol 43 (5) ◽  
pp. 545-566 ◽  
Author(s):  
Benjamin Nyblade ◽  
Angela O’Mahony ◽  
Aim Sinpeng

Traditional techniques used to study political engagement—interviews, ethnographic research, surveys—rely on collection of data at a single or a few points in time and/or from a small sample of political actors. They lead to a tendency in the literature to focus on “snapshots” of political engagement (as in the analysis of a single survey) or draw from a very limited set of sources (as in most small group ethnographic work and interviewing). Studying political engagement through analysis of social media data allows scholars to better understand the political engagement of millions of people by examining individuals’ views on politics in their own voices. While social media analysis has important limitations, it provides the opportunity to see detailed “video” of political engagement over time that provides an important complement to traditional methods. We illustrate this point by drawing on social media data analysis of the protests and election in Thailand from October 2013 through February 2014.


2018 ◽  
Vol 38 (1) ◽  
pp. 57-74 ◽  
Author(s):  
Elizabeth Dubois ◽  
Anatoliy Gruzd ◽  
Jenna Jacobson

Journalists increasingly use social media data to infer and report public opinion by quoting social media posts, identifying trending topics, and reporting general sentiment. In contrast to traditional approaches of inferring public opinion, citizens are often unaware of how their publicly available social media data are being used and how public opinion is constructed using social media analytics. In this exploratory study based on a census-weighted online survey of Canadian adults ( N = 1,500), we examine citizens’ perceptions of journalistic use of social media data. We demonstrate that (1) people find it more appropriate for journalists to use aggregate social media data rather than personally identifiable data, (2) people who use more social media are more likely to positively perceive journalistic use of social media data to infer public opinion, and (3) the frequency of political posting is positively related to acceptance of this emerging journalistic practice, which suggests some citizens want to be heard publicly on social media while others do not. We provide recommendations for journalists on the ethical use of social media data and social media platforms on opt-in functionality.


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