Using data mining to track the information spreading on social media about the COVID-19 outbreak

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yunfei Xing ◽  
Wu He ◽  
Gaohui Cao ◽  
Yuhai Li
Keyword(s):  
Social Media ◽  
User Interaction ◽  
Health Concern ◽  
Data Sets ◽  
Evolutionary Trend ◽  
Global Public Health ◽  
Content Type ◽  
Information Spreading ◽  
Using Data ◽  
Different Characteristics

Purpose COVID-19, a causative agent of the potentially fatal disease, has raised great global public health concern. Information spreading on the COVID-19 outbreak can strongly influence people behaviour in social media. This paper aims to question of information spreading on COVID-19 outbreak are addressed with a massive data analysis on Twitter from a multidimensional perspective. Design/methodology/approach The evolutionary trend of user interaction and the network structure is analysed by social network analysis. A differential assessment on the topics evolving is provided by the method of text clustering. Visualization is further used to show different characteristics of user interaction networks and public opinion in different periods. Findings Information spreading in social media emerges from different characteristics during various periods. User interaction demonstrates multidimensional cross relations. The results interpret how people express their thoughts and detect topics people are most discussing in social media. Research limitations/implications This study is mainly limited by the size of the data sets and the unicity of the social media. It is challenging to expand the data sets and choose multiple social media to cross-validate the findings of this study. Originality/value This paper aims to find the evolutionary trend of information spreading on the COVID-19 outbreak in social media, including user interaction and topical issues. The findings are of great importance to help government and related regulatory units to manage the dissemination of information on emergencies, in terms of early detection and prevention.

Improving sentiment scoring mechanism: a case study on airline services

2018 ◽  
Vol 118 (8) ◽  
pp. 1578-1596 ◽  
Author(s):  
Wandeep Kaur ◽  
Vimala Balakrishnan
Keyword(s):  
Social Media ◽  
Content Type ◽  
Exclamation Mark ◽  
Semantic Orientation ◽  
Social Media Text ◽  
Major Airlines ◽  
Using Data ◽  
Sentiment Score ◽  
Repeated Letter ◽  
Facebook Pages

Purpose The purpose of this paper is to investigate the effect of including letter repetition commonly found within social media text and its impact in determining the sentiment scores for two major airlines in Malaysia. Design/methodology/approach A Sentiment Intensity Calculator (SentI-Cal) was developed by assigning individual weights to each letter repetition, and tested it using data collected from official Facebook pages of the airlines. Findings Evaluation metrics indicate that SentI-Cal outperforms the baseline tool Semantic Orientation Calculator (SO-CAL), with an accuracy of 90.7 percent compared to 58.33 percent for SO-CAL. Practical implications A more accurate sentiment score allows airline services to easily obtain a better understanding of the sentiments of their customers, hence providing opportunities in improving their airline services. Originality/value Proposed mechanism calculates sentiment intensity of social media text by assigning individual weightage to each repeated letter and exclamation mark thus producing a more accurate sentiment score.

What the fake? Assessing the extent of networked political spamming and bots in the propagation of #fakenews on Twitter

2019 ◽  
Vol 43 (1) ◽  
pp. 53-71 ◽  
Author(s):  
Ahmed Al-Rawi ◽  
Jacob Groshek ◽  
Li Zhang
Keyword(s):  
Social Media ◽  
Data Sets ◽  
Fake News ◽  
Content Type ◽  
Mainstream Media ◽  
News Discourse ◽  
Twitter Data ◽  
News Organizations ◽  
Twitter Users ◽  
One Year

PurposeThe purpose of this paper is to examine one of the largest data sets on the hashtag use of #fakenews that comprises over 14m tweets sent by more than 2.4m users.Design/methodology/approachTweets referencing the hashtag (#fakenews) were collected for a period of over one year from January 3 to May 7 of 2018. Bot detection tools were employed, and the most retweeted posts, most mentions and most hashtags as well as the top 50 most active users in terms of the frequency of their tweets were analyzed.FindingsThe majority of the top 50 Twitter users are more likely to be automated bots, while certain users’ posts like that are sent by President Donald Trump dominate the most retweeted posts that always associate mainstream media with fake news. The most used words and hashtags show that major news organizations are frequently referenced with a focus on CNN that is often mentioned in negative ways.Research limitations/implicationsThe research study is limited to the examination of Twitter data, while ethnographic methods like interviews or surveys are further needed to complement these findings. Though the data reported here do not prove direct effects, the implications of the research provide a vital framework for assessing and diagnosing the networked spammers and main actors that have been pivotal in shaping discourses around fake news on social media. These discourses, which are sometimes assisted by bots, can create a potential influence on audiences and their trust in mainstream media and understanding of what fake news is.Originality/valueThis paper offers results on one of the first empirical research studies on the propagation of fake news discourse on social media by shedding light on the most active Twitter users who discuss and mention the term “#fakenews” in connection to other news organizations, parties and related figures.

scholarly journals Could Dampening Expression of theNeisseria gonorrhoeaemtrCDE-Encoded Efflux Pump Be a Strategy To Preserve Currently or Resurrect Formerly Used Antibiotics To Treat Gonorrhea?

mBio ◽  
2019 ◽  
Vol 10 (4) ◽  
Author(s):  
Shaochun Chen ◽  
Kristie L. Connolly ◽  
Corinne Rouquette-Loughlin ◽  
Alexander D’Andrea ◽  
Ann E. Jerse ◽  
...  
Keyword(s):  
Genital Tract ◽  
Efflux Pump ◽  
Health Concern ◽  
Third Generation ◽  
Global Public Health ◽  
Beta Lactam ◽  
Beta Lactams ◽  
Genital Tract Infection ◽  
Infected Female ◽  
Content Type

ABSTRACTNeisseria gonorrhoeaehas developed resistance to every antibiotic introduced for treatment of gonorrhea since 1938, and concern now exists that gonorrheal infections may become refractory to all available antibiotics approved for therapy. The current recommended dual antibiotic treatment regimen of ceftriaxone (CRO) and azithromycin (AZM) is threatened with the emergence of gonococcal strains displaying resistance to one or both of these antibiotics. Non-beta-lactamase resistance to penicillin and third-generation cephalosporins, as well as low-level AZM resistance expressed by gonococci, requires overexpression of themtrCDE-encoded efflux pump, which in wild-type (WT) strains is subject to transcriptional repression by MtrR. Since earlier studies showed that loss of MtrCDE renders gonococci hypersusceptible to beta-lactams and macrolides, we hypothesized that transcriptional dampening ofmtrCDEwould render an otherwise resistant strain susceptible to these antibiotics as assessed by antibiotic susceptibility testing and during experimental infection. In order to test this hypothesis, we ectopically expressed a WT copy of themtrRgene, which encodes the repressor of themtrCDEefflux pump operon, inN. gonorrhoeaestrain H041, the first reported gonococcal strain to cause a third-generation-cephalosporin-resistant infection. We now report that MtrR production can repress the expression ofmtrCDE, increase antimicrobial susceptibilityin vitro, and enhance beta-lactam efficacy in eliminating gonococci as assessed in a female mouse model of lower genital tract infection. We propose that strategies that target the MtrCDE efflux pump should be considered to counteract the increasing problem of antibiotic-resistant gonococci.IMPORTANCEThe emergence of gonococcal strains resistant to past or currently used antibiotics is a global public health concern, given the estimated 78 million infections that occur annually. The dearth of new antibiotics to treat gonorrhea demands that alternative curative strategies be considered to counteract antibiotic resistance expressed by gonococci. Herein, we show that decreased expression of a drug efflux pump that participates in gonococcal resistance to antibiotics can increase gonococcal susceptibility to beta-lactams and macrolides under laboratory conditions, as well as improve antibiotic-mediated clearance of gonococci from the genital tract of experimentally infected female mice.

scholarly journals Characteristics of Gun Advertisements on Social Media: Systematic Search and Content Analysis of Twitter and YouTube Posts (Preprint)

2019 ◽  
Author(s):  
Lisa Jordan ◽  
James Kalin ◽  
Colleen Dabrowski
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Systematic Search ◽  
Health Concern ◽  
Corporate Ownership ◽  
Public Health Concern ◽  
Social Media Platforms ◽  
Streaming Services ◽  
Youtube Videos ◽  
Different Characteristics

BACKGROUND Although gun violence has been identified as a major public health concern, the scope and significance of internet gun advertising is not known. OBJECTIVE This study aimed to quantify the characteristics of gun advertising on social media and to compare the reach of posts by manufacturers with those of influencers. METHODS Using a systematic search, we created a database of recent and popular Twitter and YouTube posts made public by major firearm manufacturers and influencers. From our sample of social media posts, we reviewed the content of the posts on the basis of 19 different characteristics, such as type of gun, presence of women, and military or police references. Our content analysis summarized statistical differences in the information conveyed in posts to compare advertising approaches across social media platforms. RESULTS Sample posts revealed that firearm manufacturers use social media to attract audiences to websites that sell firearms: 14.1% (131/928; ±2.9) of Twitter posts, 53.6% (228/425; ±6.2) of YouTube videos, and 89.5% (214/239; ±5.1) of YouTube influencer videos link to websites that facilitate sales. Advertisements included women in efforts to market handguns and pistols for the purpose of protection: videos with women included protection themes 2.5 times more often than videos without women. Top manufacturers of domestic firearms received 98 million channel views, compared with 6.1 billion channel views received by the top 12 YouTube influencers. CONCLUSIONS Firearm companies use social media as an advertising platform to connect viewers to websites that sell guns. Gun manufacturers appropriate YouTube servers, video streaming services, and the work of YouTube influencers to reach large audiences to promote the widespread sale of consumer firearms. YouTube and Twitter subsidize gun advertising by offering server and streaming services at no cost to gun manufacturers, to the commercial benefit of Google and Twitter’s corporate ownership.

A Framework for the Forensic Analysis of User Interaction with Social Media

2012 ◽  
Vol 4 (4) ◽  
pp. 15-30 ◽  
Author(s):  
John Haggerty ◽  
Mark C. Casson ◽  
Sheryllynne Haggerty ◽  
Mark J. Taylor
Keyword(s):  
Social Media ◽  
User Interaction ◽  
Large Data ◽  
Forensic Analysis ◽  
Data Sets ◽  
User Engagement ◽  
Online Data ◽  
Use Of Social Media ◽  
Temporal Dimensions ◽  
Media Applications

The increasing use of social media, applications or platforms that allow users to interact online, ensures that this environment will provide a useful source of evidence for the forensics examiner. Current tools for the examination of digital evidence find this data problematic as they are not designed for the collection and analysis of online data. Therefore, this paper presents a framework for the forensic analysis of user interaction with social media. In particular, it presents an inter-disciplinary approach for the quantitative analysis of user engagement to identify relational and temporal dimensions of evidence relevant to an investigation. This framework enables the analysis of large data sets from which a (much smaller) group of individuals of interest can be identified. In this way, it may be used to support the identification of individuals who might be ‘instigators’ of a criminal event orchestrated via social media, or a means of potentially identifying those who might be involved in the ‘peaks’ of activity. In order to demonstrate the applicability of the framework, this paper applies it to a case study of actors posting to a social media Web site.

scholarly journals Novel Genes Related to Ceftriaxone Resistance Found among Ceftriaxone-Resistant Neisseria gonorrhoeae Strains SelectedIn Vitro

2016 ◽  
Vol 60 (4) ◽  
pp. 2043-2051 ◽  
Author(s):  
Zijian Gong ◽  
Wei Lai ◽  
Min Liu ◽  
Zhengshuang Hua ◽  
Yayin Sun ◽  
...  
Keyword(s):  
Neisseria Gonorrhoeae ◽  
Resistance Mechanisms ◽  
Health Concern ◽  
Cross Resistance ◽  
Growth Time ◽  
Single Mutation ◽  
Global Public Health ◽  
Differential Analysis ◽  
Content Type ◽  
Genes Encoding

ABSTRACTThe emergence of ceftriaxone-resistantNeisseria gonorrhoeaeis currently a global public health concern. However, the mechanism of ceftriaxone resistance is not yet fully understood. To investigate the potential genes related to ceftriaxone resistance inNeisseria gonorrhoeae, we subcultured six gonococcal strains with increasing concentrations of ceftriaxone and isolated the strains that became resistant. After analyzing several frequently reported genes involved in ceftriaxone resistance, we found only a single mutation inpenA(A501V). However, differential analysis of the genomes and transcriptomes between pre- and postselection strains revealed many other mutated genes as well as up- and downregulated genes. Transformation of the mutatedpenAgene into nonresistant strains increased the MIC between 2.0- and 5.3-fold, and transformation of mutatedftsXincreased the MIC between 3.3- and 13.3-fold. Genes encoding the ABC transporters FarB, Tfq, Hfq, and ExbB were overexpressed, whilepilM,pilN, andpilQwere downregulated. Furthermore, the resistant strain developed cross-resistance to penicillin and cefuroxime, had an increased biochemical metabolic rate, and presented fitness defects such as prolonged growth time and downregulated PilMNQ. In conclusion, antimicrobial pressure could result in the emergence of ceftriaxone resistance, and the evolution of resistance ofNeisseria gonorrhoeaeto ceftriaxone is a complicated process at both the pretranscriptional and posttranscriptional levels, involving several resistance mechanisms of increased efflux and decreased entry.

Digitalization and migration: the role of social media and migrant networks in migration decisions. An exploratory study in Nigeria

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chinedu Obi ◽  
Fabio Bartolini ◽  
Marijke D’Haese
Keyword(s):  
Social Media ◽  
Information Asymmetry ◽  
Structural Equation ◽  
Equation Model ◽  
Content Type ◽  
Migrant Networks ◽  
Awareness Campaigns ◽  
Using Data ◽  
And Migration

Purpose This paper aims to explore the connectivity between social media use, access to migrant networks, information asymmetry and migration intentions. Design/methodology/approach The study was conducted using data from individuals living in Nigeria and analysed with a generalized structural equation model, which is rare for this kind of research. Findings The authors find a dual mediating role of the social media and the migrant networks in facilitating migration, i.e. reducing the threshold cost required to migrate and introducing a bias in terms of information asymmetry. While social media and access to migrant networks directly increase migration intentions, this changes when incomplete information is provided. People who use social media and their migrant networks for information are more likely to have information about destination countries than information on the transit risk. Social implications The study adds valuable insights for designing awareness campaigns aimed at reducing irregular migration. Originality/value This study contributes to the understanding of the intersection of migration and digitalization

scholarly journals A Tale of Two Institutions: COVID-19 Positive Rates in Asymptomatic Patients Pre-Screened for Spine Procedures and Surgeries in Los Angeles, California

2021 ◽  
pp. 219256822110574
Author(s):  
Allen S. Chen ◽  
Matthew Brown ◽  
Anush Arekelyan ◽  
Sophie Wennemann ◽  
Nick Shamie ◽  
...  
Keyword(s):  
Public Health ◽  
Los Angeles ◽  
Los Angeles County ◽  
Data Sets ◽  
Global Public Health ◽  
Rt Pcr ◽  
Asymptomatic Patients ◽  
Time Period ◽  
Chi Squared ◽  
Using Data

Study Design Retrospective cohort study. Objectives The coronavirus disease (COVID-19), caused by the severe respiratory syndrome coronavirus 2 (SARS-CoV-2), has created an unprecedented global public health emergency. The aim of the current study was to report on COVID-19 rates in an asymptomatic population prior to undergoing spine procedures or surgeries at two large Los Angeles healthcare systems. Methods Elective spine procedures and surgeries from May 1, 2020 to January 31, 2021 were included. Results from SARS-CoV-2 virus RT-PCR nasopharyngeal testing within 72 hours prior to elective spine procedures were recorded. Los Angeles County COVID-19 rates were calculated using data sets from Los Angeles County Department of Public Health. Chi-squared test and Stata/IC were used for statistical analysis. Results A total of 4,062 spine procedures and surgeries were scheduled during this time period. Of these, 4,043 procedures and surgeries were performed, with a total of 19 patients testing positive. Nine positive patients were from UCLA, and 10 from USC. The overall rate of positive tests was low at .47% and reflected similarities with Los Angeles County COVID-19 rates over time. Conclusions The current study shows that pre-procedure COVID-19 testing rates remains very low, and follows similar patterns of community rates. While pre-procedure testing increases the safety of elective procedures, universal COVID-19 pre-screening adds an additional barrier to receiving care for patients and increases cost of delivering care. A combination of pre-screening, pre-procedure self-quarantine, and consideration of overall community COVID-19 positivity rates should be further studied.

Business Models and Transactions in C2C Social Commerce: Practices of Selected Social Commerce Practitioners in Thailand

2018 ◽  
Vol 15 (06) ◽  
pp. 1850048
Author(s):  
Atchara Leeraphong ◽  
Borworn Papasratorn
Keyword(s):  
Social Media ◽  
Business Models ◽  
User Interaction ◽  
Interaction Patterns ◽  
Social Commerce ◽  
Direct Observations ◽  
Transaction Process ◽  
User Interaction Patterns ◽  
Different Characteristics ◽  
Logical Process

There has been an increase in the popularity of using social media for commercial purposes, and this is commonly known as consumer-to-consumer (C2C) social commerce (s-commerce). Thailand is among one of the world’s largest C2C s-commerce markets; however, its C2C s-commerce has different characteristics from traditional e-commerce. This study investigated the patterns of various C2C s-commerce business models and purchasing processes being used in Thailand, based on data collection from interviews and direct observations. The findings revealed the patterns of the transaction process, including advertising, searching, negotiation and ordering, payment, and delivery. It also been found that there are six business models in C2C s-commerce: S-retailing, S-specific market, S-preorder, S-auction, S-reverse auction, and S-portal. The activities in C2C s-commerce were presented by using the logical process diagram to show differences in user interaction patterns and business arrangements. A solid understanding of business models and purchasing processes will help sellers to improve process effectiveness, as well as helping buyers reduce the risk when making purchases using C2C s-commerce in Thailand.

Typology of social media followers: the case of luxury brands

2018 ◽  
Vol 36 (5) ◽  
pp. 558-571 ◽  
Author(s):  
Zahy Ramadan ◽  
Maya F. Farah ◽  
Armig Dukenjian
Keyword(s):  
Social Media ◽  
Design Methodology ◽  
Qualitative Approach ◽  
Luxury Brands ◽  
Content Type ◽  
Luxury Brand ◽  
Different Types ◽  
Social Media Platforms ◽  
Different Characteristics ◽  
Depth Interviews

Purpose Luxury brands tend to be hesitant in adopting social media. This matter has created an imminent need to understand the different types of online luxury followers so as to help luxury brands communicate effectively with their consumers, while maintaining the “luxe” image and experience. Accordingly, the purpose of this paper is to provide luxury brands with a deeper understanding of their online audience and the strategies needed to engage with them through the different social media platforms. Design/methodology/approach A qualitative approach was utilized in which 24 in-depth interviews were conducted with Lebanese followers of an online luxury brand’s social media pages. Findings The study identifies the presence of six main categories of online luxury followers: pragmatists, bystanders, trend hunters, image seekers, passionate owners, and prime consumers. Each group has a specific engagement and propensity to buy levels. Research limitations/implications Understanding the different segments of luxury brand followers provides a framework for marketing managers that allows them to correctly target their marketing and communication strategies in order to maximize consumer engagement and purchasing behaviors. Originality/value A significant gap exists in the extant literature which offers no understanding of the different luxury brand followers and their different characteristics. This study is the first to offer an exploratory typology of the various luxury brand followers on social media platforms.

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