Commercial Websites Research Articles

A Multimetric Evaluation of Online Patient Educational Materials for Breast Implant-associated Anaplastic Large Cell Lymphoma.

To assess understandability, actionability, and readability of online patient educational materials (OPEM) related to breast implant-associated anaplastic large cell lymphoma (BIA-ALCL). Search volumes for query terms related to BIA-ALCL including "breast implant associated lymphoma," "breast implant associated anaplastic large cell lymphoma," and "BIA-ALCL" were analyzed in one-week increments and normalized to total Google search volume. The same terms were then queried using an online search engine to identify commonly accessed OPEM on this topic. Understandability and actionability of OPEM were evaluated using the Patient Education Materials Assessment Tool. Grade-level readability was determined using generalized estimating equations, with observations nested within readability metrics from each website. All interval estimates were calculated for 95% confidence. Overall, 24 websites were identified based on search parameters. Of these websites, 11 (45.8%) met criteria for understandability, and 1 (4.2%) met criteria for actionability. Overall, readability ranged from 10.2 to 17.3 for all websites with an average grade level readability of 12.4; 0 websites were written at or below a sixth-grade reading level. Government websites had the highest average grade reading level at 14.0, followed by commercial websites at 13.2, nonprofit websites at 12.0, and then academic/hospital-based websites at 11.5. The quality of available OPEM on BIA-ALCL is limited. Future development of OPEM should be designed with the goal of improving both comprehension and actionability to help reduce patient anxiety and unnecessary clinical appointments related to this disease.

Geotourism Destinations Online Branding Co-Creation

The application of brand theory to destinations has grown in the last few decades, with the destination brand personality being a viable metaphor for creating and positioning destination brands. An often-overlooked tourism typology is geotourism; more specifically, volcanic tourism, since it can be a passive element of any tourism form or active nature tourism. However, its potential is relatively unexplored in terms of online branding. For this reason, the present study analyzes online brand image co-creation, using 300 websites related to three unique volcanic tourism destinations—Iceland, the Azores, and the Canary Islands. Three different types of sources (destination marketing organizations, commercial, and editorial websites) created these contents. The results demonstrate significant differences between the communication of the three destinations, with Iceland, where there is less aligned communication, most valuing geo elements in their communication, and the Azores, where all stakeholders communicate similar brand personality traits, displaying more aligned communication regarding brand personality. In the Canary Islands geotourism is less explored as a destination offer and is consequently less communicated. Acknowledging the different brand positioning and the parity and differentiation points among destinations with the same baseline offer—volcanic tourism—can be helpful for destination brand managers to reignite tourism and promote a unique tourism experience.

What Yelp Fake Review Filter Might Be Doing?

Online reviews have become a valuable resource for decision making. However, its usefulness brings forth a curse ‒ deceptive opinion spam. In recent years, fake review detection has attracted significant attention. However, most review sites still do not publicly filter fake reviews. Yelp is an exception which has been filtering reviews over the past few years. However, Yelp’s algorithm is trade secret. In this work, we attempt to find out what Yelp might be doing by analyzing its filtered reviews. The results will be useful to other review hosting sites in their filtering effort. There are two main approaches to filtering: supervised and unsupervised learning. In terms of features used, there are also roughly two types: linguistic features and behavioral features. In this work, we will take a supervised approach as we can make use of Yelp’s filtered reviews for training. Existing approaches based on supervised learning are all based on pseudo fake reviews rather than fake reviews filtered by a commercial Web site. Recently, supervised learning using linguistic n-gram features has been shown to perform extremely well (attaining around 90% accuracy) in detecting crowdsourced fake reviews generated using Amazon Mechanical Turk (AMT). We put these existing research methods to the test and evaluate performance on the real-life Yelp data. To our surprise, the behavioral features perform very well, but the linguistic features are not as effective. To investigate, a novel information theoretic analysis is proposed to uncover the precise psycholinguistic difference between AMT reviews and Yelp reviews (crowdsourced vs. commercial fake reviews). We find something quite interesting. This analysis and experimental results allow us to postulate that Yelp’s filtering is reasonable and its filtering algorithm seems to be correlated with abnormal spamming behaviors.

The benefit of online education in twin-to-twin transfusion syndrome: could it be an eye-opening platform?

Objective This study intends to objectively review the quality and reliability of laser photocoagulation for twin-to-twin transfusion syndrome (TTTS) videos on the YouTube® platform in terms of integrity and educational value for patients and medical professionals. Methods YouTube® (http://www.youtube.com) search was performed for videos pertaining to fetal laser surgery in TTTS, using the terms fetoscopic laser ablation or/and fetoscopic laser surgery or/and fetoscopic laser twin-to-twin transfusion syndrome. A total of 42 videos were analyzed. Video sources were categorized as follows: INDIVIDUAL, ACADEMIC INSTITUTION, and COMMERCIAL. Source of videos, time since upload (days), total duration of videos (seconds), total views, and likes were recorded. Video power index (VPI) was used to report video popularity. Educational quality and integrity were reviewed using the DISCERN, JAMA, GQS, and a novel YouTube® TTTS content - integrity score (TTTS-IS). Results The mean duration was 336.43±351.8 seconds, and the total views were 172.076±82.6. Surgical risks were stated only in 33% of videos, and the success rate of surgery was mentioned in 35%. In all groups, the median value of DISCERN scores is 32.50, 42, and 26, which refers to poor, fair, and very poor quality, respectively. Videos uploaded by an academic institution had statistically insignificant DISCERN and JAMA scores along with lower GQS and TTTS-IS (p>0.05). In regards to the video source, academic institutions were prominent (47.6%), and the most popularized videos were conducted by commercial websites and individuals related to VPI. The VPI was poorly correlated with all scoring systems. Negative correlations were detected between total views and JAMA scores and positive correlations were determined with the GQS and TTTS-IS. Conclusion Despite having VPI score highly in each group, YouTube® provides low-quality videos regarding fetal laser surgery of TTTS. There is an urgent need to regulate the context of those videos according to medical guidelines.

Understanding the role of visuals in commercial website interaction on smartphone display

Flexible and ease of internet access through mobile device in Indonesia has changed the way users interact with commercial websites, especially online ticketing service website. Yet, no study on how the presented website visuals on smartphone display perceived and experienced by users is found. This paper exposes users’ interactive experience on smartphone display, showcasing 3 (three) popular online ticketing service providers in Indonesia, traveloka dot com, pegi-pegi dot com, and tiket dot com. 60 individuals were purposively sampled and each was asked to access all chosen websites using provided smartphone. 2 (two) pages follow-up questionnaire was presented to each respondent: first page is for identifying users’ perception 5 (five) items likert-scale responses and second page is for identifying users’ experiences using Schrepp, Hinderks & Thomaschewski’s UXQ (User Experience Questionnaire). Results show that when interacting with online ticketing service websites on smartphone, sites that look simple and easy to interact with may provide sense of savvyness, comfortability, and security. This indicates that presented website visuals on smartphone display affect users’ experience when using online services. Although further studies are needed, this results offer valuable insights to the discussions of human interactive experience in using online platform.

A content analysis of scald first aid information on Chinese websites

ObjectiveWith the rapid development of networks in China, the Internet has become an important source of first aid information for scalds. As a country with the largest population, there are a large number of scald cases every year in China. The content analysis of websites aimed to assess the accuracy and quality of the information on scalds available on Chinese websites. MethodsUsing keywords related to scald in the most popular Chinese search engines, 19 sites were eventually selected for evaluation based on the inclusion and exclusion criteria. These websites were assessed on quality and content accuracy by using HONcode, DISCERN, and Patient Education Materials Assessment Tool (PEMAT) evaluation scales, and a modified evaluation system based on the system developed by J.D. Burgess. The evaluation was completed by a 5-person evaluation team. The subjective items were reviewed by five independent reviewers. The objective items were recorded by one reviewer, then another checked the results. ResultsUsing “scald first aid,” “scald treatment,” and “scald blister” to search on Baidu, Sougou, and Haosou, a total of 180 websites were recorded. According to the inclusion and exclusion criteria, 19 websites were obtained for assessment. Among them, 17 websites (89%) were established by commercial companies. Of the remaining two websites, one was created by a government agency and the other was created by a non-profit organization. The mean total HONcode score, DISCERN score, PEMAT (understandability) score, PEMAT (actionability) score, content accuracy score, and website quality score were 5.19 ± 1.09 out of 8; 52.63 ± 3.69 out of 80; 68%; 56%; 5.05 ± 1.47 out of 8; and 6.11 out of 12, respectively. The scores of the government agency website are better than that of commercial websites. ConclusionThe websites established by government agencies and non-profit organizations are few, and most of the websites are established by commercial companies. Compared with the government agency website, these commercial websites contain many advertisements, and their website quality and accuracy need to be further improved.

Exploring energy-saving refrigerators through online e-commerce reviews: an augmented mining model based on machine learning methods

PurposeBased on climate issues and carbon emissions, this study aims to promote low-carbon consumption and compel consumers to actively shift to energy-saving appliances. In this big data era, online reviews in social and electronic commerce (e-commerce) websites contain valuable product information, which can facilitate firm business strategies and consumer comparison shopping. This study is designed to advance existing research on energy-saving refrigerators by incorporating machine learning models in the analysis of online reviews to provide valuable suggestions to e-commerce platform managers and manufacturers to effectively understand the psychological cognition of consumers.Design/methodology/approachThis study proposes an online e-commerce review mining and management strategy model based on “data acquisition and cleaning, data mining and analysis and strategy formation” through multiple machine learning methods, namely, Bayes networks, support vector machine (SVM), latent Dirichlet allocation (LDA) and importance–performance analysis (IPA), to help managers.FindingsBased on a case study of one of the largest e-commerce platforms in China, this study linguistically analyzes 29,216 online reviews of energy-saving refrigerators. Results indicate that the energy-saving refrigerator features that consumers are generally satisfied with are, in sequential order, logistics, function, price, outlook, after-sales service, brand, quality and space. This study also identifies ten topics with 100 keywords by analyzing 18 different refrigerator models. Finally, based on the IPA, this study allocates different priorities to the features and provides suggestions from the perspective of consumers, the government and manufacturers.Research limitations/implicationsIn terms of limitations, future research may focus on the following points. First, the topics identified in this study derive from specific points in time and reviews; thus, the topics may change with the text data. A machine learning-based online review analysis platform could be developed in the future to dynamically improve consumer satisfaction. Moreover, given that consumers' needs may change over time, e-commerce platform types and consumer characteristics, such as user profiles, can be incorporated into the model to effectively analyze trends in consumers' perceived dimensions.Originality/valueThis study fills the gap in previous research in this field, which uses small-sample data for qualitative analysis, while integrating management ideas and proposes an online e-commerce review mining and management strategy model based on machine learning methods. Moreover, this study considers how consumers' emotional and thematic preferences for products affect their purchase decision-making from the perspective of their psychological perception and linguistically analyzes online reviews of energy-saving refrigerators using the proposed mining model. Through the improved IPA model, this study provides optimizing strategies to help e-commerce platform managers and manufacturers.

E-Commerce Marketing Strategy & Industrial Packaging Design to Increase Profit for Bontang Manggrove Syrup Products in Tanjung Laut Indah Village, Bontang City

The business industry of the product of the fruit syrup ovata mangrove is an effort belonging to Ibu Amirah, the head of the Fragrant Leaf group (Paguyuban usaha Mangrove village in Tanjung Laut Indah, South Bontang, Bontang City, East Kalimantan province. In the implementation of the activities successfully identified and resolved several problems of the partner namely processing, the provision of business tools processing of mangrove syrup, identification of packaging design shortage, advertisement production of mangrove fruit syrup in the e-site Commerce and demonstration of how to process e commerce and social media sites. In the overall stages of activity, the team of devotion also coordinates and interviews with the forestry service of the province of East Kalimantan which became the authorized institution in the management of the mangrove fruit syrup and its cultivation in the city of Bontang. Hopefully in this stage, partners can independently add products, conduct sales control, and use e commerce sites to the fullest without relying on the team.

PENCARIAN PRODUK E-COMMERCE BERDASARKAN JUDUL DAN DESKRIPSI MENGGUNAKAN VECTOR SPACE MODEL

E-Commerce in Indonesia has increased every year, especially B2C sales and this is directly proportional to the increasing number of e-commerce sites in Indonesia. One of the things that this site offers is the ease of finding the product you want to find. However, in several tests conducted, it turns out that some Indonesian e commerce sites are unable to search for products based on the description keyword. Therefore, the writer tries to do this research using the VSM algorithm and produces an accuracy of 60%, a precision of 72.73%, and a recall of 80%.

Dermatology 2.0- How the Internet is Changing us, our Patients and our Practice.

The internet, in a short span of time relative to the history of modern medicine, has changed us doctors, our patients and our practice. This article reviews these changes and how they have occurred. The write- up was conceptualized after the authors started noticing subtle and overt differences in the consultation and treatment paths of patients who were internet savvy vs. those who were internet naïve. A survey was conducted in the clinic to understand the behavioral changes brought about by the internet among patients of clinical as well as aesthetic dermatology. It must be remembered that these changes are completely new to the practice of dermatology; even small numbers of positive replies are noteworthy. The Covid 19 pandemic has made teledermatology a requisite of the time, rather than an option. Our dependence on technology has never before been so profound. As modern-day dermatologists, we need to be updated about the interactions of dermatology and technology. We must constantly try to optimize the benefits of the internet and minimize its pitfalls. Needless to say, most of the facts mentioned here have been gleaned from the internet itself, from a wide range of sources including but not limited to medical journals, books, news reports, commercial websites and magazines.

A hybrid semi-supervised boosting to sentiment analysis

In this article, we propose a hybrid semi-supervised boosting algorithm to sentiment analysis. Semi-supervised learning is a learning task from a limited amount of labeled data and plenty of unlabeled data which is the case in our used dataset. The proposed approach employs the classifier predictions along with the similarity information to assign label to unlabeled examples. We propose a hybrid model based on the agreement among different constructed classification model based on the boosting framework to assign a final label to unlabeled data. The proposed approach employs several different similarity measurements in its loss function to show the role of the similarity function. We further address the main preprocessing steps in the used dataset. Our experimental results on real-world microblog data from a commercial website show that the proposed approach can effectively exploit information from the unlabeled data and significantly improves the classification performance.

Evaluation of Readability of Turkish Websites About Smoking Cessation

Objective: This study aimed to examine the readability levels and contents of Turkish websites on smoking cessation. Method: A search was performed in August 2019 by typing the word “smoking cessation” in Google search engine (https://www.google.com). Commercial websites, advertisement websites, chat websites, forum websites, magazine websites, websites containing only images or videos, and websites with less than 10 sentences were excluded from the study. The readability levels of Turkish websites on smoking cessation were determined according to the Ateşman and Bezirci-Yılmaz readability formulas. Results: A total of 62 websites (23 (37.1%) in the first group and 39 (62.9%) in the second group) were included in the study. The median Ateşman and Bezirci-Yılmaz readability values were respectively 48.47 and 13.08. The median number of sentences was 34.00. The median number of words was 439.00. Conclusion: This study found that the readability level of Turkish websites on smoking cessation was “difficult” according to the Ateşman readability formula and at “undergraduate level” according to the Bezirci-Yılmaz readability formula. These results are fairly higher than the education level of Turkish people.

Recent Developments in Medicated Lozenges: A Promising Dosage Form for the Effective Delivery of Therapeutic Agents

:The delivery of therapeutic agents through the oral route remains the most favorable one as compared to other routes of drug administration. However, numerous disadvantages are encountered in conventional formulations such as low bioavailability, first-pass metabolism, gastric irritation, delayed onset of action, bitter taste, low retention time, frequent dosing, and non-localized drug targeting. All these problems encountered guide the various pharmaceutical industries to manufacture and develop a novel solid oral dosage form called lozenges. Lozenges are solid oral dosage forms of medicament, meant to be dissolved within the mouth or pharynx. They may consist of one or more than one medicinal agent in a sweetened and flavored base material.:The present review is focused on various types, compositions, and methodologies used to prepare the medicated lozenges and on different evaluation parameters that establish their safety and efficacy. It also put a light on different commercially available and reported medicated lozenges formulation.:The various review and research articles reported by different researchers were studied extensively by using the databases of Google Scholar, Pubmed, Scopus, Web of Science and various commercial websites that were also investigated for information regarding new products.:Lozenges provide various advantages in terms of patient compliance, rapid onset of action, prolonged retention time, enhancement of bioavailability, ease of manufacturing, localized drug targeting, sustained or controlled effect, and reduced dosing frequency. They also have the ability to incorporate the drugs belonging to different therapeutic classes for treating various disorders related to oral cavities like gingivitis, dental plaque, mouth ulcers, throat pain, oral thrush, throat infection, periodontitis, and pharyngitis. However, its applicability is not only limited to localized action, but it has also been employed to deliver the drug systemically for the conditions such as cough, decongestion, runny nose, nausea, vomiting, allergy, low immunity, fever, body ache, the killing of worms and smoking cessation.:It was concluded that they have played an important role in the field of drug delivery and will continue to perform in the same way in the future as well.

Websites' hue-context congruence as a vector of trust and behavioral intentions

PurposeThis paper aims to determine the effect of the congruence between a website's background color and its context (product category) on online trust and resulting behavioral intentions in emerging markets.Design/methodology/approachAn online experiment, conducted on 240 web-surfers, compared two versions of a website (high vs low color-context congruence) in terms of online trust and resulting behavioral intentions. The authors also studied the moderating role of the online shopping experience on the color-context congruence impact on online trust.FindingsResults revealed that a website's color-context congruence enhances online trust. The authors have also demonstrated that online trust plays a mediating role in the relationship between color-context congruence and behavioral intentions. Moreover, they found out that the influence of the color-context congruence on online trust is enhanced when the web-surfer is highly experienced in online shopping.Research limitations/implicationsThis research contributes to fill in the theoretical gaps and to better understand the influence of color-context congruence on online trust and behavioral intentions in emerging markets. Indeed, past studies had focused on the color impact on online trust without taking into consideration congruence with the website context. However, this study is limited to a single category of products (tourist products) and only two colors (blue and red) were manipulated in the experiment.Practical implicationsThis study highlights the importance of selecting a background's color that matches with the sold product category to reassure web-surfers so that they trust the commercial website and express some favorable intentions like buying.Originality/valuePrior studies had focused on the website's color effect on online trust neglecting color-context congruence. Our study helps to highlight the importance of selecting background colors matching the product category.

Development, Status Quo, and Challenges to China's Health Informatization During COVID-19: Evaluation and Recommendations.

By applying advanced health information technology to the health care field, health informatization helps optimize health resource allocation, improve health care services, and realize universal health coverage. COVID-19 has tested the status quo of China’s health informatization, revealing challenges to the health care system. This viewpoint evaluates the development, status quo, and practice of China’s health informatization, especially during COVID-19, and makes recommendations to address the health informatization challenges. We collected, assessed, and evaluated data on the development of China’s health informatization from five perspectives—health information infrastructure, information technology (IT) applications, financial and intellectual investment, health resource allocation, and standard system—and discussed the status quo of the internet plus health care service pattern during COVID-19. The main data sources included China’s policy documents and national plans on health informatization, commercial and public welfare sources and websites, public reports, institutional reports, and academic papers. In particular, we extracted data from the 2019 National Health Informatization Survey released by the National Health Commission in China. We found that China developed its health information infrastructure and IT applications, made significant financial and intellectual informatization investments, and improved health resource allocations. Tested during COVID-19, China’s current health informatization system, especially the internet plus health care system, has played a crucial role in monitoring and controlling the pandemic and allocating medical resources. However, an uneven distribution of health resources and insufficient financial and intellectual investment continue to challenge China’s health informatization. China’s rapid development of health informatization played a crucial role during COVID-19, providing a reference point for global pandemic prevention and control. To further promote health informatization, China’s health informatization needs to strengthen top-level design, increase investment and training, upgrade the health infrastructure and IT applications, and improve internet plus health care services.

Fraud Detection in E-Commerce Using Machine Learning

Customers rely heavily on decisions to purchase products either on commerce sites or in online retail outlets. Since these reviews are the game changers for success or failure in product marketing, reviews are used for positive or negative ideas. Improper reviews may also be referred to as false / fraudulent reviews or spam comments or false reviews. To downgrade or advance the item, resentful audits or phony surveys, which are tricky, are posted in the web-based business site. This outcome will prompt possible monetary misfortunes or bigger measure of development in business.So, the proposed system is design and developed in such way that it will detect fake, false and spam reviews for fraud detection using machine learning approaches like Sentiment Analysis, Support Vector Machine (SVM), Decision Tree algorithm, and N-gram model

E-commerce websites, consumer order fulfillment and after-sales service satisfaction: the customer is always right, even after the shopping cart check-out

PurposeThis research identifies the critical factors of online service delivery of electronic commerce (e-commerce) websites, including website attractiveness, website functionality, website security and consumer fulfillment during an unprecedented Coronavirus (COVID-19) pandemic.Design/methodology/approachA structured questionnaire was used to gather data from 430 online respondents who were members of popular social media groups. The survey instrument relied on valid and reliable measures relating to electronic service quality (e-SERVQUAL) to better understand the participants’ satisfaction with shopping websites, as well as their loyal behaviors and word-of-mouth activities.FindingsThe findings reported that consumers valued the e-commerce websites’ features and their consumer order fulfillment capabilities. These factors increase the consumers’ satisfaction with online shopping experiences, generate repeat business, as well as positive reviews on social media.Research limitations/implicationsThis study addresses a knowledge gap in academia. To date, little research has focused on the consumer order fulfillment aspect of e-commerce transactions and on after-sales of online businesses.Originality/valueThis contribution posits that e-commerce websites ought to be appealing, functional and offer secure transactions. More importantly, it suggests that merchants should consistently deliver personalized service in all stages of an online purchase, including after the delivery of the ordered products.

Which Review Can Make You Engage?

Online reviews facilitate customer brand engagement, but few studies have explored this problem from the perspective of interpersonal attraction and its psychological mechanisms in the social commerce context. This paper aims to investigate the effect of reviewer-reader similarity (including external and internal similarity) in online reviews on customer brand engagement in the social commerce context. Drawing upon the social categorization theory, a conceptual framework was developed and tested empirically. Data collected from a sample of Chinese consumers with the shopping experience on social commerce websites (N=392) was analyzed using Partial Least Square (PLS). Findings reveal that both external and internal similarities are indirectly influenced consumer brand engagement, and mediated by consumers' perceived value and congruence transferred through this process. The impact of external similarity on customer brand engagement was greater through consumers' perceived value, whereas the influence of internal similarity was stronger through consumers' self-brand congruence.

Contextual recommender system for E-commerce applications

Today’s arena of global village organizations, social applications, and commercial websites provides huge information about products, individuals, and activities. This is leading to a plethora of content that requires effective handling to obtain the desired information. A recommendation system (RS) suggests relevant items to the user according to his/her desired preference. It processes various information related to users and items. However, RSs suffer from data sparsity. Generally, deep learning techniques are used in RSs for deep analysis of item contents to create precise recommendations. However, the effective handling of user reviews in parallel with item reviews is still an open research domain that can be further explored. In this paper, a hybrid model that handles both user and item metadata concurrently is proposed with the aim of solving the sparsity problem. To demonstrate the viability of the proposed methodology, a series of experiments was performed on three real-world datasets. The results show that the proposed model outperforms other state-of-the-art approaches to the best of our knowledge.

Analysing online Twitter discussions of bedwetting via a condition-specific hashtag (#Bedwetting).

Bedwetting is a common paediatric condition. #Bedwetting has been established as the official hashtag to structure Twitter discussions about the condition. We analysed online Twitter discussions for #Bedwetting. Symplur, a Twitter analytics service was employed to aggregate Twitter activity, users and content including #Bedwetting, between October 2013 and November 2018. Activity was analysed via tweet volume and user adoption. Users were assorted using geographic location, occupation and affiliation data. Content in #Bedwetting Tweets was undertaken by retrieving information about retweets, links, frequently used words and hashtags. A total of 101 412 tweets and 9957 users utilising #Bedwetting were identified. Most tweets were sent with links (93%). The average ± SD number of tweets using #Bedwetting per month increased from 96 ± 87 in 2013 to 2935 ± 1644 in 2015. Tweet volume decreased to 1960 ± 257 in 2016 and subsequently increased to 2901 ± 1110 in 2017. New users increased from 4 in 2013 to 9957 users in 2018. Users tweeted from 69 countries. Advocacy organisations comprised 35% of the top 100 influencers. Common words in #Bedwetting tweets were 'potty', 'best' and 'training'. Popular associated hashtags were #Pottytraining, #Solutions and #Moms. Hyperlinks in #Bedwetting tweets included advocacy, academic and commercial websites. Our analysis of #Bedwetting highlights that Twitter is frequently used to discuss the condition's diagnosis and management. Various stakeholders in health care are utilising the platform to build awareness about bedwetting. We identified that Twitter is being employed to drive web traffic to other internet websites.