Google.com was the website with the most page views per day in Bolivia in February 2022, according to ranking by Alexa. The website had more than ***** daily page views and was followed by Unitel.bo, with ** page views per day that month. Within Latin America, Mexico was the country where Amazon Alexa contained the largest number of skills.

This dataset is composed of the URLs of the top 1 million websites. The domains are ranked using the Alexa traffic ranking which is determined using a combination of the browsing behavior of users on the website, the number of unique visitors, and the number of pageviews. In more detail, unique visitors are the number of unique users who visit a website on a given day, and pageviews are the total number of user URL requests for the website. However, multiple requests for the same website on the same day are counted as a single pageview. The website with the highest combination of unique visitors and pageviews is ranked the highest

Google.com, youtube.com, and facebook.com were the most visited websites in Ukraine in December 2021. Furthermore, Google's website on the Ukrainian domain, google.com.ua, ranked in the top 10 during that time.

Traffic analytics, rankings, and competitive metrics for alexa.com as of May 2025

In 2019, the Chinese marketplace Alibaba was the leading worldwide B2B e-commerce in terms of online traffic. The Alexa tool assessing the online traffic of websites put it on the top of the ranking, with a score of ***. The Russian Rosfirm and the U.S. platform Vinsuite followed in the ranking with a score of ***** and *****, respectively.

General data recollected for the studio " Analysis of the Quantitative Impact of Social Networks on Web Traffic of Cybermedia in the 27 Countries of the European Union". Four research questions are posed: what percentage of the total web traffic generated by cybermedia in the European Union comes from social networks? Is said percentage higher or lower than that provided through direct traffic and through the use of search engines via SEO positioning? Which social networks have a greater impact? And is there any degree of relationship between the specific weight of social networks in the web traffic of a cybermedia and circumstances such as the average duration of the user's visit, the number of page views or the bounce rate understood in its formal aspect of not performing any kind of interaction on the visited page beyond reading its content? To answer these questions, we have first proceeded to a selection of the cybermedia with the highest web traffic of the 27 countries that are currently part of the European Union after the United Kingdom left on December 31, 2020. In each nation we have selected five media using a combination of the global web traffic metrics provided by the tools Alexa (https://www.alexa.com/), which ceased to be operational on May 1, 2022, and SimilarWeb (https:// www.similarweb.com/). We have not used local metrics by country since the results obtained with these first two tools were sufficiently significant and our objective is not to establish a ranking of cybermedia by nation but to examine the relevance of social networks in their web traffic. In all cases, cybermedia whose property corresponds to a journalistic company have been selected, ruling out those belonging to telecommunications portals or service providers; in some cases they correspond to classic information companies (both newspapers and televisions) while in others they refer to digital natives, without this circumstance affecting the nature of the research proposed.
Below we have proceeded to examine the web traffic data of said cybermedia. The period corresponding to the months of October, November and December 2021 and January, February and March 2022 has been selected. We believe that this six-month stretch allows possible one-time variations to be overcome for a month, reinforcing the precision of the data obtained. To secure this data, we have used the SimilarWeb tool, currently the most precise tool that exists when examining the web traffic of a portal, although it is limited to that coming from desktops and laptops, without taking into account those that come from mobile devices, currently impossible to determine with existing measurement tools on the market. It includes:

Web traffic general data: average visit duration, pages per visit and bounce rate Web traffic origin by country Percentage of traffic generated from social media over total web traffic Distribution of web traffic generated from social networks Comparison of web traffic generated from social netwoks with direct and search procedures

Dataset

This dataset was created by DNS_dataset

Contents

The people from Czech are publishing a dataset for the HTTPS traffic classification.

Since the data were captured mainly in the real backbone network, they omitted IP addresses and ports. The datasets consist of calculated from bidirectional flows exported with flow probe Ipifixprobe. This exporter can export a sequence of packet lengths and times and a sequence of packet bursts and time. For more information, please visit ipfixprobe repository (Ipifixprobe).

During research, they divided HTTPS into five categories: L -- Live Video Streaming, P -- Video Player, M -- Music Player, U -- File Upload, D -- File Download, W -- Website, and other traffic.

They have chosen the service representatives known for particular traffic types based on the Alexa Top 1M list and Moz's list of the most popular 500 websites for each category. They also used several popular websites that primarily focus on the audience in Czech. The identified traffic classes and their representatives are provided below:

Live Video Stream Twitch, Czech TV, YouTube Live Video Player DailyMotion, Stream.cz, Vimeo, YouTube Music Player AppleMusic, Spotify, SoundCloud File Upload/Download FileSender, OwnCloud, OneDrive, Google Drive Website and Other Traffic Websites from Alexa Top 1M list

We are publishing a dataset we created for the HTTPS traffic classification.

Since the data were captured mainly in the real backbone network, we omitted IP addresses and ports. The datasets consist of calculated from bidirectional flows exported with flow probe Ipifixprobe. This exporter can export a sequence of packet lengths and times and a sequence of packet bursts and time. For more information, please visit ipfixprobe repository (Ipifixprobe).

During our research, we divided HTTPS into five categories: L -- Live Video Streaming, P -- Video Player, M -- Music Player, U -- File Upload, D -- File Download, W -- Website, and other traffic.

We have chosen the service representatives known for particular traffic types based on the Alexa Top 1M list and Moz's list of the most popular 500 websites for each category. We also used several popular websites that primarily focus on the audience in our country. The identified traffic classes and their representatives are provided below:

Live Video Stream Twitch, Czech TV, YouTube Live

Video Player DailyMotion, Stream.cz, Vimeo, YouTube

Music Player AppleMusic, Spotify, SoundCloud

File Upload/Download FileSender, OwnCloud, OneDrive, Google Drive

Website and Other Traffic Websites from Alexa Top 1M list

In November 2021, Agt.se was the most popular website in Sweden based on user engagement with an average session length of about ** minutes and ** seconds. Facebook.com was ranked second with users spending approximately ** minutes and ** seconds per visit to the platform.

We present a dataset targeting a large set of popular pages (Alexa top-500), from probes from several ISPs networks, browsers software (Chrome, Firefox) and viewport combinations, for over 200,000 experiments realized in 2019.We purposely collect two distinct sets with two different tools, namely Web Page Test (WPT) and Web View (WV), varying a number of relevant parameters and conditions, for a total of 200K+ web sessions, roughly equally split among WV and WPT. Our dataset comprises variations in terms of geographical coverage, scale, diversity and representativeness (location, targets, protocol, browser, viewports, metrics).For Web Page Test, we used the online service www.webpagetest.org at different locations worldwide (Europe, Asia, USA) and private WPT instances in three locations in China (Beijing, Shanghai, Dongguan). The list of target URLs comprised the main pages and five random subpages from Alexa top-500 worldwide and China. We varied network conditions : native connections and 4G, FIOS, 3GFast, DSL, and custom shaping/loss conditions. The other elements in the configuration were fixed: Chrome browser on desktop with a fixed screen resolution, HTTP/2 protocol and IPv4.For Web View, we collected experiments from three machines located in France. We selected two versions of two browser families (Chrome 75/77, Firefox 63/68), two screen sizes (1920x1080, 1440x900), and employ different browser configurations (one half of the experiments activate the AdBlock plugin) from two different access technologies (fiber and ADSL). From a protocol standpoint, we used both IPv4 and IPv6, with HTTP/2 and QUIC, and performed repeated experiments with cached objects/DNS. Given the settings diversity, we restricted the number of websites to about 50 among the Alexa top-500 websites, to ensure statistical relevance of the collected samples for each page.The two archives IFIPNetworking2020_WebViewOrange.zip and IFIPNetworking2020_Webpagetest.zip correspond respectively to the Web View experiments and to the Web Page Test experiments.Each archive contains three files:- config.csv: Description of parameters and conditions for each run,- metrics.csv: Value of different metrics collected by the browser,- progressionCurves.csv: Progression curves of the bytes progress as seen by the network, from 0 to 10 seconds by steps of 100 milliseconds,- listUrl folder: Indexes the sets of urls.Regarding config.csv, the columns are: - index: Index for this set of conditions, - location: Location of the machine, - listUrl: List of urls, located in the folder listUrl - browserUsed: Internet browser and version - terminal: Desktop or Mobile - collectionEnvironment: Identification of the collection environment - networkConditionsTrafficShaping (WPT only): Whether native condition or traffic shaping (4G, FIOS, 3GFast, DSL, or custom Emulator conditions) - networkConditionsBandwidth (WPT only): Bandwidth of the network - networkConditionsDelay (WPT only): Delay in the network - networkConditions (WV only): network conditions - ipMode (WV only): requested L3 protocol, - requestedProtocol (WV only): requested L7 protocol - adBlocker (WV only): Whether adBlocker is used or not - winSize (WV only): Window sizeRegarding metrics.csv, the columns are: - id: Unique identification of an experiment (consisting of an index 'set of conditions' and an index 'current page') - DOM Content Loaded Event End (ms): DOM time, - First Paint (ms) (WV only): First paint time, - Load Event End (ms): Page Load Time from W3C, - RUM Speed Index (ms) (WV only): RUM Speed Index, - Speed Index (ms) (WPT only): Speed Index, - Time for Full Visual Rendering (ms) (WV only): Time for Full Visual Rendering - Visible portion (%) (WV only): Visible portion, - Time to First Byte (ms) (WPT only): Time to First Byte, - Visually Complete (ms) (WPT only): Visually Complete used to compute the Speed Index, - aatf: aatf using ATF-chrome-plugin - bi_aatf: bi_aatf using ATF-chrome-plugin - bi_plt: bi_plt using ATF-chrome-plugin - dom: dom using ATF-chrome-plugin - ii_aatf: ii_aatf using ATF-chrome-plugin - ii_plt: ii_plt using ATF-chrome-plugin - last_css: last_css using ATF-chrome-plugin - last_img: last_img using ATF-chrome-plugin - last_js: last_js using ATF-chrome-plugin - nb_ress_css: nb_ress_css using ATF-chrome-plugin - nb_ress_img: nb_ress_img using ATF-chrome-plugin - nb_ress_js: nb_ress_js using ATF-chrome-plugin - num_origins: num_origins using ATF-chrome-plugin - num_ressources: num_ressources using ATF-chrome-plugin - oi_aatf: oi_aatf using ATF-chrome-plugin - oi_plt: oi_plt using ATF-chrome-plugin - plt: plt using ATF-chrome-pluginRegarding progressionCurves.csv, the columns are: - id: Unique identification of an experiment (consisting of an index 'set of conditions' and an index 'current page') - url: Url of the current page. SUBPAGE stands for a path. - run: Current run (linked with index of the config for WPT) - filename: Filename of the pcap - fullname: Fullname of the pcap - har_size: Size of the HAR for this experiment, - pagedata_size: Size of the page data report - pcap_size: Size of the pcap - App Byte Index (ms): Application Byte Index as computed from the har file (in the browser) - bytesIn_APP: Total bytes in as seen in the browser, - bytesIn_NET: Total bytes in as seen in the network, - X_BI_net: Network Byte Index computed from the pcap file (in the network) - X_bin_0_for_B_completion to X_bin_99_for_B_completion: X_bin_k_for_B_completion is the bytes progress reached after k*100 millisecondsIf you use these datasets in your research, you can reference to the appropriate paper:@inproceedings{qoeNetworking2020, title={Revealing QoE of Web Users from Encrypted Network Traffic}, author={Huet, Alexis and Saverimoutou, Antoine and Ben Houidi, Zied and Shi, Hao and Cai, Shengming and Xu, Jinchun and Mathieu, Bertrand and Rossi, Dario}, booktitle={2020 IFIP Networking Conference (IFIP Networking)}, year={2020}, organization={IEEE}}

The Amazon Echo is the most prevalent smart speaker in households in the United States in 2020. **** million Amazon Echos make up the installed base in the United States, a share of more than ** percent of the total smart speaker installed base.

From September to November 2023, adult entertainment websites Xvideos.com and Pornhub.com were the websites with the most pages per visit in Norway, with an average of 8.1 and 7.5 pages visited per session. Additionally, visitors to Finn.no accessed approximately 6.5 pages per visit. Social video platform YouTube.com Ranked fourth with 6.2 pages per visit.

As of May 2019, Google had the highest reach among services web properties. The website is currently among the top 10 websites in Vietnam in the Alexa ranking.

As of May 2019, Shopee.vn had the highest reach among retail web properties. The website is currently among the top 10 websites in Vietnam in the Alexa ranking.

As of May 2019, Facebook had the highest reach among social media web properties. The website is currently among the top 10 websites in Vietnam in the Alexa ranking.

As of May 2019, Kenh14.vn had the highest reach among entertainment web properties. The website covers content relating to entertainment and society and addresses mostly teenagers. It is currently among the top 20 websites in Vietnam in the Alexa ranking.

The Alexa rank of nykaa.com moved from 4.8 thousand to more than seven thousand between January and March 2021. This indicated a decrease in the popularity of the website. In comparison, purplle.com, one of Nykaa's competitors, ranked at around 25 thousand, while Myntra ranked at about one thousand.

Am 23. Juni führte WordPress das Ranking der Top 10 Content-Management-Systeme (CMS) weltweit nach Marktanteil mit **** Prozent an. Shopify hatte einen Marktanteil von rund *** Prozent und lag damit auf dem zweiten Rang der verbreitetsten Content-Management-Systeme. Es wurden die Top-10-Millionen Websites (Alexa-Ranking) in die Erhebung einbezogen, Subdomains wurden bei der Zählung nicht berücksichtigt. Was sind Content-Management-Systeme? Content-Management-Systeme (CMS) ermöglichen es Nutzern ohne oder mit wenig Programmier- bzw. HTML-Kenntnissen Internetseiten mit geringem Aufwand zu erstellen und diese mit Inhalten zu füllen. Solche Inhalte können aus Text- und Multimedia-Dokumenten bestehen. Je nach Verwendungszweck und Anwendungsgebiet stehen unterschiedliche CMS zur Verfügung. WordPress WordPress gehört zu den am verbreitetsten, freien Content-Management-Systemen. Es wurde ursprünglich als Blog-Publishing-System entwickelt, hat sich jedoch weiterentwickelt, um auch andere Arten von Web-Inhalten zu unterstützen, darunter traditionellere Mailinglisten und Foren, Mediengalerien, Mitglieder-Websites, Learning-Management-Systeme (LMS) und Online-Shops. Diverse Anwendungsgebiete ermöglichen es WordPress, den weltweit größten Marktanteil unter CMS zu haben. Dies führt wiederum dazu, dass insgesamt rund ** Millionen Blog-Posts von WordPress-Nutzern im August 2024 veröffentlicht wurden. Dazu lag die Anzahl der Page Views von WordPress-Artikeln zuletzt bei rund **** Milliarden.

Im Juli 2025 nutzten **** Prozent aller untersuchten Webseiten WordPress als Content-Management-System. Mit großem Abstand folgten Shopify auf dem zweiten Platz mit einem Nutzungsanteil von *** Prozent und Wix mit rund *** Prozent auf Platz drei. Content-Management-Systeme nach Marktanteil Im Juni 2025 führte WordPress das Ranking der Top 10 Content-Management-Systeme (CMS) weltweit mit einem Marktanteil von über ** Prozent an. Shopify hatte einen Marktanteil von über ***** Prozent und lag damit auf dem zweiten Rang der verbreitetsten Content-Management-Systeme. Es wurden die Top-10-Millionen Websites (Alexa-Ranking) in die Erhebung einbezogen, Subdomains wurden bei der Zählung nicht berücksichtigt. WordPress WordPress ist ein weitverbreitetes, freies Content-Management-System. Es wurde ursprünglich als Blog-Publishing-System entwickelt, hat sich jedoch weiterentwickelt, um auch andere Arten von Web-Inhalten zu unterstützen, darunter traditionellere Mailinglisten und Foren, Mediengalerien, Mitglieder-Websites, Learning-Management-Systeme (LMS) und Online-Shops. Diverse Anwendungsgebiete haben es WordPress ermöglicht, den weltweit größten Marktanteil unter den CMS zu haben. Dies führt wiederum dazu, dass insgesamt rund ** Millionen Blog-Posts von WordPress-Nutzern im August 2024 veröffentlicht wurden. Dazu lag die Anzahl der Page Views von WordPress-Artikeln im Januar 2025 bei rund **** Milliarden.