Social media content and sentiment analysis on consumer security breaches

2016 ◽  
Vol 23 (4) ◽  
pp. 855-869 ◽  
Author(s):  
Jianqiang Hao ◽  
Hongying Dai
Keyword(s):  
Social Media ◽  
Empirical Study ◽  
Sentiment Analysis ◽  
Real Time ◽  
Public Perception ◽  
Public Awareness ◽  
Content Type ◽  
Security Breaches ◽  
Short Period ◽  
Significant Difference

Purpose Security breaches have been arising issues that cast a large amount of financial losses and social problems to society and people. Little is known about how social media could be used a surveillance tool to track messages related to security breaches. This paper aims to fill the gap by proposing a framework in studying the social media surveillance on security breaches along with an empirical study to shed light on public attitudes and concerns. Design/methodology/approach In this study, the authors propose a framework for real-time monitoring of public perception to security breach events using social media metadata. Then, an empirical study was conducted on a sample of 1,13,340 related tweets collected in August 2015 on Twitter. By text mining a large number of unstructured, real-time information, the authors extracted topics, opinions and knowledge about security breaches from the general public. The time series analysis suggests significant trends for multiple topics and the results from sentiment analysis show a significant difference among topics. Findings The study confirms that social media monitoring provides a supplementary tool for the traditional surveys which are costly and time-consuming to track security breaches. Sentiment score and impact factors are good predictors of real-time public opinions and attitudes to security breaches. Unusual patterns/events of security breaches can be detected in the early stage, which could prevent further destruction by raising public awareness. Research limitations/implications The sample data were collected from a short period of time on Twitter. Future study could extend the research to a longer period of time or expand key words search to observe the sentiment trend, especially before and after large security breaches, and to track various topics across time. Practical implications The findings could be useful to inform public policy and guide companies responding to consumer security breaches in shaping public perception. Originality/value This study is the first of its kind to undertake the analysis of social media (Twitter) content and sentiment on public perception to security breaches.

scholarly journals COVID-19 SENTIMENT ANALYSIS ON FACEBOOK COMMENTS

2021 ◽  
Vol 4 (17) ◽  
pp. 01-08
Author(s):  
Sajidah Ibrahim ◽  
Nor Zairah Ab Rahim ◽  
Fajar Ibnu Fatihan ◽  
Nur Azaliah Abu Bakar
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Public Perception ◽  
Public Awareness ◽  
Movement Control ◽  
Positive Thinking ◽  
User Comments ◽  
Areas Of Concern ◽  
The Government ◽  
Control Order

Malaysia recorded its first COVID-19 case on 9th March 2020 and recorded a total of 59,817 by end of November 2020. Buzz in social media over COVID-19 and measures by the Government to curb infection spread among citizens. The study aims to understand Malaysian public awareness and perception of COVID-19 related issues on Facebook during the 1st and 2nd week of Movement Control Order (MCO). Data mining was conducted on DG Tan Sri Noor Hisham Abdullah’s official Facebook account user comments and a total of 77,351 comments was collected between 18 March and 14 April 2020. The analyses included data pre-processing and sentiment analysis to identify and explore sentiments in discussion topics within the first two weeks of lockdown. The results yield majority of comments are in the Malay language and mix languages of English and Malay as a secondary type. Secondly, sentiment analysis showed that people have a positive reaction towards the frontliners and all efforts by the Ministry of Health towards fighting the pandemic. Many positive remarks are given in form of prayers, which is in line with the Islamic teaching of positive thinking and optimism, especially during crises. In conclusion, sentiment analysis is effective in producing useful insights about trends of COVID-19 discussion on social media, collecting public perception and feedback of COVID-19 efforts by the Government, and gives a different viewing angle of the current situation on the ground. These findings can be useful for health officials or the Government in developing communication mitigation plans or conduct extensive studies on pertaining issues within areas of concern.

A sentiment analysis of who participates, how and why, at social media sport websites

2016 ◽  
Vol 40 (6) ◽  
pp. 814-833 ◽  
Author(s):  
Marina Bagić Babac ◽  
Vedran Podobnik
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Men And Women ◽  
Male And Female ◽  
Content Type ◽  
Premier League ◽  
User Comments ◽  
Football Clubs ◽  
Significant Difference ◽  
Facebook Pages

Purpose Due to an immense rise of social media in recent years, the purpose of this paper is to investigate who, how and why participates in creating content at football websites. Specifically, it provides a sentiment analysis of user comments from gender perspective, i.e. how differently men and women write about football. The analysis is based on user comments published on Facebook pages of the top five 2015-2016 Premier League football clubs during the 1st and the 19th week of the season. Design/methodology/approach This analysis uses a data collection via social media website and a sentiment analysis of the collected data. Findings Results show certain unexpected similarities in social media activities between male and female football fans. A comparison of the user comments from Facebook pages of the top five 2015-2016 Premier League football clubs revealed that men and women similarly express hard emotions such as anger or fear, while there is a significant difference in expressing soft emotions such as joy or sadness. Originality/value This paper provides an original insight into qualitative content analysis of male and female comments published at social media websites of the top five Premier League football clubs during the 1st and the 19th week of the 2015-2016 season.

scholarly journals Social media and sentiment in bioenergy consultation

2016 ◽  
Vol 10 (1) ◽  
pp. 87-98 ◽  
Author(s):  
Victoria Uren ◽  
Daniel Wright ◽  
James Scott ◽  
Yulan He ◽  
Hassan Saif
Keyword(s):  
Social Media ◽  
New Media ◽  
Sentiment Analysis ◽  
Opinion Mining ◽  
Public Consultation ◽  
Short Paper ◽  
Consultation Process ◽  
Content Type ◽  
The Public ◽  
The Uk

Purpose – This paper aims to address the following challenge: the push to widen participation in public consultation suggests social media as an additional mechanism through which to engage the public. Bioenergy companies need to build their capacity to communicate in these new media and to monitor the attitudes of the public and opposition organizations towards energy development projects. Design/methodology/approach – This short paper outlines the planning issues bioenergy developments face and the main methods of communication used in the public consultation process in the UK. The potential role of social media in communication with stakeholders is identified. The capacity of sentiment analysis to mine opinions from social media is summarised and illustrated using a sample of tweets containing the term “bioenergy”. Findings – Social media have the potential to improve information flows between stakeholders and developers. Sentiment analysis is a viable methodology, which bioenergy companies should be using to measure public opinion in the consultation process. Preliminary analysis shows promising results. Research limitations/implications – Analysis is preliminary and based on a small dataset. It is intended only to illustrate the potential of sentiment analysis and not to draw general conclusions about the bioenergy sector. Social implications – Social media have the potential to open access to the consultation process and help bioenergy companies to make use of waste for energy developments. Originality/value – Opinion mining, though established in marketing and political analysis, is not yet systematically applied as a planning consultation tool. This is a missed opportunity.

Stairways to heaven: implementing social media in organizations

2013 ◽  
Vol 17 (5) ◽  
pp. 741-754 ◽  
Author(s):  
Moria Levy
Keyword(s):  
Social Media ◽  
Knowledge Management ◽  
Empirical Study ◽  
Design Methodology ◽  
Applied Research ◽  
Service Marketing ◽  
Content Type ◽  
Four Levels ◽  
Functional Components ◽  
Practical Implications

Purpose – This paper is aimed at both researchers and organizations. For researchers, it seeks to provide a means for better analyzing the phenomenon of social media implementation in organizations as a knowledge management (KM) enabler. For organizations, it seeks to suggest a step-by-step architecture for practically implementing social media and benefiting from it in terms of KM. Design/methodology/approach – The research is an empirical study. A hypothesis was set; empirical evidence was collected (from 34 organizations). The data were analyzed both quantitatively and qualitatively, thereby forming the basis for the proposed architecture. Findings – Implementing social media in organizations is more than a yes/no question; findings show various levels of implementation in organizations: some implementing at all levels, while others implement only tools, functional components, or even only visibility. Research limitations/implications – Two main themes should be further tested: whether the suggested architecture actually yields faster/eased KM implementation compared to other techniques; and whether it can serve needs beyond the original scope (KM, Israel) as tested in this study (i.e. also for other regions and other needs – service, marketing and sales, etc.). Practical implications – Organizations can use the suggested four levels architecture as a guideline for implementing social media as part of their KM efforts. Originality/value – This paper is original and innovative. Previous studies describe the implementation of social media in terms of yes/no; this research explores the issue as a graded one, where organizations can and do implement social media step-by-step. The paper's value is twofold: it can serve as a foundational study for future researches, which can base their analysis on the suggested architecture of four levels of implementation. It also serves as applied research that will help organizations searching for social media implementation KM enablers.

Infodemic surrounding COVID-19: Can LIS students recognize and categorize “problematic information” types on social media?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shamima Yesmin ◽  
S.M. Zabed Ahmed
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Information Science ◽  
Wrong Answer ◽  
Student Groups ◽  
Content Type ◽  
Correct Definition ◽  
Significant Difference ◽  
Definition Of ◽  
And Task

Purpose The purpose of this paper is to investigate Library and Information Science (LIS) students’ understanding of infodemic and related terminologies and their ability to categorize COVID-19-related problematic information types using examples from social media platforms. Design/methodology/approach The participants of this study were LIS students from a public-funded university located at the south coast of Bangladesh. An online survey was conducted which, in addition to demographic and study information, asked students to identify the correct definition of infodemic and related terminologies and to categorize the COVID-related problematic social media posts based on their inherent problem characteristics. The correct answer for each definition and task question was assigned a score of “1”, whereas the wrong answer was coded as “0”. The percentages of correctness score for total and each category of definition and task-specific questions were computed. The independent sample t-test and ANOVA were run to examine the differences in total and category-specific scores between student groups. Findings The findings revealed that students’ knowledge concerning the definition of infodemic and related terminologies and the categorization of COVID-19-related problematic social media posts was poor. There was no significant difference in correctness scores between student groups in terms of gender, age and study levels. Originality/value To the best of the authors’ knowledge, this is the first time an effort was made to understand LIS students’ recognition and classification of problematic information. The findings can assist LIS departments in revising and improving the existing information literacy curriculum for students.

Public perception of COVID-19 vaccines from the digital footprints left on Twitter: analyzing positive, neutral and negative sentiments of Twitterati

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aasif Ahmad Mir ◽  
Sevukan Rathinam ◽  
Sumeer Gul
Keyword(s):  
Social Media ◽  
Public Perception ◽  
English Language ◽  
Social Issues ◽  
Application Programming Interface ◽  
Content Type ◽  
The Public ◽  
Public Reaction ◽  
Types Of Information ◽  
The Impact

PurposeTwitter is gaining popularity as a microblogging and social networking service to discuss various social issues. Coronavirus disease 2019 (COVID-19) has become a global pandemic and is discussed worldwide. Social media is an instant platform to deliberate various dimensions of COVID-19. The purpose of the study is to explore and analyze the public sentiments related to COVID-19 vaccines across the Twitter messages (positive, neutral, and negative) and the impact tweets make across digital social circles.Design/methodology/approachTo fetch the vaccine-related posts, a manual examination of randomly selected 500 tweets was carried out to identify the popular hashtags relevant to the vaccine conversation. It was found that the hashtags “covid19vaccine” and “coronavirusvaccine” were the two popular hashtags used to discuss the communications related to COVID-19 vaccines. 23,575 global tweets available in public domain were retrieved through “Twitter Application Programming Interface” (API), using “Orange Software”, an open-source machine learning, data visualization and data mining toolkit. The study was confined to the tweets posted in English language only. The default data cleaning and preprocessing techniques available in the “Orange Software” were applied to the dataset, which include “transformation”, “tokenization” and “filtering”. The “Valence Aware Dictionary for sEntiment Reasoning” (VADER) tool was used for classification of tweets to determine the tweet sentiments (positive, neutral and negative) as well as the degree of sentiments (compound score also known as sentiment score). To assess the influence/impact of tweets account wise (verified and unverified) and sentiment wise (positive, neutral, and negative), the retweets and likes, which offer a sort of reward or acknowledgment of tweets, were used.FindingsA gradual decline in the number of tweets over the time is observed. Majority (11,205; 47.52%) of tweets express positive sentiments, followed by neutral (7,948; 33.71%) and negative sentiments (4,422; 18.75%), respectively. The study also signifies a substantial difference between the impact of tweets tweeted by verified and unverified users. The tweets related to verified users have a higher impact both in terms of retweets (65.91%) and likes (84.62%) compared to the tweets tweeted by unverified users. Tweets expressing positive sentiments have the highest impact both in terms of likes (mean = 10.48) and retweets (mean = 3.07) compared to those that express neutral or negative sentiments.Research limitations/implicationsThe main limitation of the study is that the sentiments of the people expressed over one single social platform, that is, Twitter have been studied which cannot generalize the global public perceptions. There can be a variation in the results when the datasets from other social media platforms will be studied.Practical implicationsThe study will help to know the people's sentiments and beliefs toward the COVID-19 vaccines. Sentiments that people hold about the COVID-19 vaccines are studied, which will help health policymakers understand the polarity (positive, negative, and neutral) of the tweets and thus see the public reaction and reflect the types of information people are exposed to about vaccines. The study can aid the health sectors to intensify positive messages and eliminate negative messages for an enhanced vaccination uptake. The research can also help design more operative vaccine-advocating communication by customizing messages using the obtained knowledge from the sentiments and opinions about the vaccines.Originality/valueThe paper focuses on an essential aspect of COVID-19 vaccines and how people express themselves (positively, neutrally and negatively) on Twitter.

scholarly journals Imported feminism: problematizing the Westernized image of the feminist in Arab social media

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ramy Magdy ◽  
Maries Mikhael ◽  
Yassmine G. Hussein
Keyword(s):  
Social Media ◽  
New Media ◽  
Real Time ◽  
Arab Women ◽  
Content Type ◽  
Second Wave Feminism ◽  
Women Experiences ◽  
Facebook Pages ◽  
The Impact ◽  
Second Wave

Purpose This paper aims to analyze the discourse of Arab feminism social media pages as a form of real-time new media. This is to be conducted culturally to understand the Westernized character these pages tend to propagate and the politico-cultural significations of such a propagation. Design/methodology/approach Using visual and content analysis the paper analyzes both the written and visual contents of two popular Arab feminist Facebook pages, “Thory” and “Feminist doodles” to explore its culture relevance/Westernization via the categories of “re-employing the binary second wave feminism, the historical relevance and the Westernized tone of both pages. Findings The pages showed a tendency toward second wave, Westernized, anti-orient feminism. Such importation of feminism made the pages’ message not only a bit irrelevant but also conceptually violent to a large extent. Starting from alien contexts, the two pages dislocate the Arab women experiences of their situation for the sake of comprehending and adapting to heavily Westernized images. Originality/value The paper contributes to the ongoing debate over the gender issue in the Arab context after 2011, what it originally offers is discussing the cultural relevance of popular feminist Facebook pages claiming to represent the everyday struggles of the Arab women. In addition, it shows the impact of real-time media on identity formulation.

scholarly journals SENTIMENT ANALYSIS FOR SARCASTIC MESSAGES IN SOCIAL MEDIA USING DEEP LEARNING TECHNIQUES - AN EMPIRICAL STUDY

2021 ◽  
Vol 9 (2) ◽  
pp. 1051-1052
Author(s):  
K. Kavitha, Et. al.
Keyword(s):  
Social Media ◽  
Deep Learning ◽  
Empirical Study ◽  
Sentiment Analysis ◽  
Learning Strategies ◽  
Language Processing ◽  
The People ◽  
Learning Techniques ◽  
Key Terms ◽  
Learning Frameworks

Sentiments is the term of opinion or views about any topic expressed by the people through a source of communication. Nowadays social media is an effective platform for people to communicate and it generates huge amount of unstructured details every day. It is essential for any business organization in the current era to process and analyse the sentiments by using machine learning and Natural Language Processing (NLP) strategies. Even though in recent times the deep learning strategies are becoming more familiar due to higher capabilities of performance. This paper represents an empirical study of an application of deep learning techniques in Sentiment Analysis (SA) for sarcastic messages and their increasing scope in real time. Taxonomy of the sentiment analysis in recent times and their key terms are also been highlighted in the manuscript. The survey concludes the recent datasets considered, their key contributions and the performance of deep learning model applied with its primary purpose like sarcasm detection in order to describe the efficiency of deep learning frameworks in the domain of sentimental analysis.

scholarly journals On Using Social Media to Predict Elections. A Meta-Analysis

2021 ◽  
Author(s):  
Brent Pretty
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Best Practices ◽  
Real Time ◽  
Public Perception ◽  
Meta Analysis ◽  
Campaign Strategy ◽  
Current State ◽  
Methods And Techniques ◽  
Analyze Data

As of late there's been great interest in social media’s ability to predict elections. Platforms such as Twitter and Facebook, owing to their cultural ubiquity, offer a plethora of data and an opportunity to track public perception at a granular level in real time. The ability to passively analyze public opinion is a massive step forward in the realm of political prediction, and has the potential to redefine the field of campaign strategy. In this piece of research I analyzed the current state of social media based electoral prediction. I examined the methods and techniques used to collect and analyze data, and compared their results against both each other and other methods of prediction such as telephone polling. In this I found a field that is still in its infancy. Much work remains to be done until a set of best practices surrounding social media based electoral prediction are accumulated.

scholarly journals Islamic banking: an exploratory study of public perception in Uganda

2018 ◽  
Vol 9 (3) ◽  
pp. 336-352 ◽  
Author(s):  
Sulaiman Lujja ◽  
Mustafa Omar Mohammed ◽  
Rusni Hassan
Keyword(s):  
Public Perception ◽  
Public Awareness ◽  
Third Party ◽  
Islamic Banking ◽  
Content Type ◽  
Muslim Minority ◽  
Fertile Ground ◽  
Muslim Majority ◽  
Remarkable Progress ◽  
Analyze Data

PurposeIslamic banking (IB) has been globally embraced by over 76 countries, with over $2tn in assets. Despite this remarkable progress, there are countries that are yet to fully embrace IB (Uganda inclusive). All the ongoing initiatives in Uganda (at policy level) to establish IB require supporting study of public awareness and attitudes toward IB. This will stimulate a down-top approach to the feasibility of IB and policymaking, thus providing a fertile ground for wider consideration of the majority stakeholders’ views in formulating standards and policy guidelines regulating IB. This study aims to explore the perception of Ugandans towards IB. Design/methodology/approachThe study is exploratory in nature and uses a quantitative method. Out of the 400 questionnaires distributed, only 354 were usable for further analysis. SPSS 21 was used to analyze data using descriptive statistics and factor analysis. FindingsMajor findings indicate that unlike non-Muslims, Muslims are more knowledgeable about the IB culture, although both groups have low awareness about IB terminologies. There were inconsistences in Muslim and non-Muslim attitudes toward IB, for instance; while non-Muslims are motivated by “profitability”, Muslims’ inclination to IB is mainly due to “religious and profitability combined”. Both groups demonstrated some uniformity in their selection criteria of banks such as “third party influence”, although they are inconsistent in other factors. Originality/valueThe novelty of this study rests in its down-top approach to feasibility of IB by gauging the perception of majority stakeholders before IB is established. The study is conducted in a heterogeneous society unlike many of similar studies that have focused on Muslim majority countries. As most studies (with similar background) are at least 18 years old, this study remains outstanding in gauging the dynamics of stakeholders in Muslim minority countries which have yet established IB.

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