Author: Víctor Yeste. Universitat Politècnica de Valencia.The object of this study is the design of a cybermetric methodology whose objectives are to measure the success of the content published in online media and the possible prediction of the selected success variables.In this case, due to the need to integrate data from two separate areas, such as web publishing and the analysis of their shares and related topics on Twitter, has opted for programming as you access both the Google Analytics v4 reporting API and Twitter Standard API, always respecting the limits of these.The website analyzed is hellofriki.com. It is an online media whose primary intention is to solve the need for information on some topics that provide daily a vast number of news in the form of news, as well as the possibility of analysis, reports, interviews, and many other information formats. All these contents are under the scope of the sections of cinema, series, video games, literature, and comics.This dataset has contributed to the elaboration of the PhD Thesis:Yeste Moreno, VM. (2021). Diseño de una metodología cibermétrica de cálculo del éxito para la optimización de contenidos web [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/176009Data have been obtained from each last-minute news article published online according to the indicators described in the doctoral thesis. All related data are stored in a database, divided into the following tables:tesis_followers: User ID list of media account followers.tesis_hometimeline: data from tweets posted by the media account sharing breaking news from the web.status_id: Tweet IDcreated_at: date of publicationtext: content of the tweetpath: URL extracted after processing the shortened URL in textpost_shared: Article ID in WordPress that is being sharedretweet_count: number of retweetsfavorite_count: number of favoritestesis_hometimeline_other: data from tweets posted by the media account that do not share breaking news from the web. Other typologies, automatic Facebook shares, custom tweets without link to an article, etc. With the same fields as tesis_hometimeline.tesis_posts: data of articles published by the web and processed for some analysis.stats_id: Analysis IDpost_id: Article ID in WordPresspost_date: article publication date in WordPresspost_title: title of the articlepath: URL of the article in the middle webtags: Tags ID or WordPress tags related to the articleuniquepageviews: unique page viewsentrancerate: input ratioavgtimeonpage: average visit timeexitrate: output ratiopageviewspersession: page views per sessionadsense_adunitsviewed: number of ads viewed by usersadsense_viewableimpressionpercent: ad display ratioadsense_ctr: ad click ratioadsense_ecpm: estimated ad revenue per 1000 page viewstesis_stats: data from a particular analysis, performed at each published breaking news item. Fields with statistical values can be computed from the data in the other tables, but total and average calculations are saved for faster and easier further processing.id: ID of the analysisphase: phase of the thesis in which analysis has been carried out (right now all are 1)time: "0" if at the time of publication, "1" if 14 days laterstart_date: date and time of measurement on the day of publicationend_date: date and time when the measurement is made 14 days latermain_post_id: ID of the published article to be analysedmain_post_theme: Main section of the published article to analyzesuperheroes_theme: "1" if about superheroes, "0" if nottrailer_theme: "1" if trailer, "0" if notname: empty field, possibility to add a custom name manuallynotes: empty field, possibility to add personalized notes manually, as if some tag has been removed manually for being considered too generic, despite the fact that the editor put itnum_articles: number of articles analysednum_articles_with_traffic: number of articles analysed with traffic (which will be taken into account for traffic analysis)num_articles_with_tw_data: number of articles with data from when they were shared on the media’s Twitter accountnum_terms: number of terms analyzeduniquepageviews_total: total page viewsuniquepageviews_mean: average page viewsentrancerate_mean: average input ratioavgtimeonpage_mean: average duration of visitsexitrate_mean: average output ratiopageviewspersession_mean: average page views per sessiontotal: total of ads viewedadsense_adunitsviewed_mean: average of ads viewedadsense_viewableimpressionpercent_mean: average ad display ratioadsense_ctr_mean: average ad click ratioadsense_ecpm_mean: estimated ad revenue per 1000 page viewsTotal: total incomeretweet_count_mean: average incomefavorite_count_total: total of favoritesfavorite_count_mean: average of favoritesterms_ini_num_tweets: total tweets on the terms on the day of publicationterms_ini_retweet_count_total: total retweets on the terms on the day of publicationterms_ini_retweet_count_mean: average retweets on the terms on the day of publicationterms_ini_favorite_count_total: total of favorites on the terms on the day of publicationterms_ini_favorite_count_mean: average of favorites on the terms on the day of publicationterms_ini_followers_talking_rate: ratio of followers of the media Twitter account who have recently published a tweet talking about the terms on the day of publicationterms_ini_user_num_followers_mean: average followers of users who have spoken of the terms on the day of publicationterms_ini_user_num_tweets_mean: average number of tweets published by users who spoke about the terms on the day of publicationterms_ini_user_age_mean: average age in days of users who have spoken of the terms on the day of publicationterms_ini_ur_inclusion_rate: URL inclusion ratio of tweets talking about terms on the day of publicationterms_end_num_tweets: total tweets on terms 14 days after publicationterms_ini_retweet_count_total: total retweets on terms 14 days after publicationterms_ini_retweet_count_mean: average retweets on terms 14 days after publicationterms_ini_favorite_count_total: total bookmarks on terms 14 days after publicationterms_ini_favorite_count_mean: average of favorites on terms 14 days after publicationterms_ini_followers_talking_rate: ratio of media Twitter account followers who have recently posted a tweet talking about the terms 14 days after publicationterms_ini_user_num_followers_mean: average followers of users who have spoken of the terms 14 days after publicationterms_ini_user_num_tweets_mean: average number of tweets published by users who have spoken about the terms 14 days after publicationterms_ini_user_age_mean: the average age in days of users who have spoken of the terms 14 days after publicationterms_ini_ur_inclusion_rate: URL inclusion ratio of tweets talking about terms 14 days after publication.tesis_terms: data of the terms (tags) related to the processed articles.stats_id: Analysis IDtime: "0" if at the time of publication, "1" if 14 days laterterm_id: Term ID (tag) in WordPressname: Name of the termslug: URL of the termnum_tweets: number of tweetsretweet_count_total: total retweetsretweet_count_mean: average retweetsfavorite_count_total: total of favoritesfavorite_count_mean: average of favoritesfollowers_talking_rate: ratio of followers of the media Twitter account who have recently published a tweet talking about the termuser_num_followers_mean: average followers of users who were talking about the termuser_num_tweets_mean: average number of tweets published by users who were talking about the termuser_age_mean: average age in days of users who were talking about the termurl_inclusion_rate: URL inclusion ratio

Location for style sheets etc used in WordPress. Wordpress is used for the Workshop Presentations display page. Or at least it will be if I can make this work...

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Cite our paper here: Segmentation of Libraries, CMS, and PHP Frameworks Based on Code Characteristics: Implementation of Clustering Using K-Means https://doi.org/10.1109/ICITRI62858.2024.10699032

This dataset contains list of PHP frameworks, CMS, and libraries that can be used to a machine learning such as clustering implementation using kmeans or other machine learning algorithm implementations.

Column Description

Application Software | Application Software | Description | | --- | --- | | Laravel | A PHP framework for elegant web application development with expressive syntax. | | yii | A high-performance PHP framework suitable for large-scale web application development. | | yii2 | The latest version of Yii, providing powerful and flexible tools for modern web application development. | | fuel | A flexible, fast, and community-focused PHP framework. | | pixie | Lightweight and fast PHP micro-framework suitable for small and medium projects. | | cakephp | A PHP framework that provides an MVC architecture for building strong and maintainable web applications. | | joomla-cms | Open-source content management system (CMS) that helps in creating websites and online applications. | | drupal | A flexible and scalable open-source CMS suitable for community websites and corporate portals. | | magento2 | An open-source e-commerce platform that gives full flexibility and control to store owners. | | ExpressionEngine | A flexible CMS that provides full control over content design and structure. | | cmsmadesimple2 | A simple and fast CMS suitable for small to medium-sized websites. | | parsedown | A PHP library for parsing Markdown quickly and efficiently. | | filp/whoops | A PHP library that provides a developer-friendly and easy-to-read stack trace. | | intervention/image | A PHP library for easy-to-use image manipulation. | | lionsoul2014/ip2region | A library for locating geographical regions based on IP addresses with high accuracy. | | PHP-CS-Fixer | A tool to fix PHP coding standards according to PSR (PHP Standards Recommendations). | | slim | A PHP micro-framework that helps in developing simple and fast web applications. | | Laravel-Excel | An extension for Laravel that makes managing Excel files easy. | | jwtauth | A library for managing JSON Web Tokens (JWT) in PHP applications. | | getgrav | A modern, lightweight, and easily customizable flat-file based CMS. | | flarum | A simple and modern open-source discussion platform. | | sage | A starter theme for WordPress built with Bootstrap and Composer. | | PhpSpreadSheet | A PHP library for reading and writing spreadsheets in various formats, including Excel and CSV. | | composer | A dependency manager for PHP that allows you to manage libraries and packages in your project. | | Faker | A PHP library for generating fake (dummy) data for testing. | | guzzle | An HTTP client library for PHP, making integration with web services and APIs easier. | | DesignPatternsPHP | A collection of examples of various design patterns implemented in PHP. | | monolog | A logging library for PHP that supports various log handlers and formats. | | yaf | A high-performance PHP framework, written in C, for web application development. | | phpredis | A PHP extension for Redis that provides an interface to interact with the Redis server. |

Feature List and Description | No | Feature | Description | | --- | --- | --- | | 1 | Directories | Number of Folders | | 2 | Files | Number of Files | | 3 | Lines of Code (LOC) | Number of lines of code | | 4 | Comment Lines of Code (CLOC) | Number of lines of code as comments | | 5 | Non-Comment Lines of Code (NCLOC) | Number of lines of code that are not comments | | 6 | Logical Lines of Code (LLOC) | Number of logical lines of code | | 7 | Classes | Number of classes | | 8 | Average Class Length | Average length of class code lines | | 9 | Minimum Class Length | Fewest number of class code lines | | 10 | Maximum Class Length | Largest number of class code lines | | 11 | Average Method Length | Average number of lines of code in functions/methods | | 12 | Minimum Method Length | Fewest number of function/method code lines | | 13 | Maximum Method Length | Largest number of function/method code lines | | 14 | Average Methods Per Class | Average number of code lines in functions/methods | | 15 | Minimum Methods Per Class | Fewest number of function/method code lines per class | | 16 | Maximum Methods Per Class | Largest number of function/method code lines per class | | 17 | Functions | Number of functions | | 18 | Average Function Length | Average number of code lines in functions | | 19 | Not in classes or functions | Number of code lines not inside classes or functions | | 20 | Average Complexity per LLOC | Average complexity per logical line of code | | 21 | Average Complexity per Class | Average complexity per class | | 22 | Minimum Cl...