3 datasets found
  1. Dynamic web page change content detection

    • zenodo.org
    Updated Apr 30, 2025
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    Damir Pozderac; Damir Pozderac; Ehlimana Cogo; Ehlimana Cogo; Irfan Prazina; Irfan Prazina; Emir Cogo; Emir Cogo; Šeila Bećirović; Šeila Bećirović; Vensada Okanovic; Vensada Okanovic (2025). Dynamic web page change content detection [Dataset]. http://doi.org/10.5281/zenodo.12699013
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    Dataset updated
    Apr 30, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Damir Pozderac; Damir Pozderac; Ehlimana Cogo; Ehlimana Cogo; Irfan Prazina; Irfan Prazina; Emir Cogo; Emir Cogo; Šeila Bećirović; Šeila Bećirović; Vensada Okanovic; Vensada Okanovic
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset contains 4 parts. "SimilarWeb dataset with screenshots" is created by scraping web elements, their CSS, and corresponding screenshots in three different time intervals for around 100 web pages. Based on this data, the "SimilarWeb dataset with SSIM column" is created with the target column containing the structural similarity index measure (SSIM) of the captured screenshots. This part of the dataset is used to train machine learning regression models. To evaluate approach, "Accessible web pages dataset" and "General use web pages dataset" parts of the dataset are used.

  2. Data from: Analysis of the Quantitative Impact of Social Networks General...

    • figshare.com
    • produccioncientifica.ucm.es
    doc
    Updated Oct 14, 2022
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    David Parra; Santiago Martínez Arias; Sergio Mena Muñoz (2022). Analysis of the Quantitative Impact of Social Networks General Data.doc [Dataset]. http://doi.org/10.6084/m9.figshare.21329421.v1
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    docAvailable download formats
    Dataset updated
    Oct 14, 2022
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    David Parra; Santiago Martínez Arias; Sergio Mena Muñoz
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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

  3. Yahoo Finance - Industries - Dataset

    • kaggle.com
    Updated May 13, 2023
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    Belayet HossainDS (2023). Yahoo Finance - Industries - Dataset [Dataset]. http://doi.org/10.34740/kaggle/dsv/5678079
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 13, 2023
    Dataset provided by
    Kaggle
    Authors
    Belayet HossainDS
    Description

    https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcSO20g5cBn_b3UvD4HrPSKMrujGXq8LfT2NQP3LC3F3k8ufSV6TP97l7Har-625Bju08bc&usqp=CAU" alt="File:Yahoo Finance Logo 2013.svg - Wikipedia">

    Yahoo! Finance is a media property that is part of the Yahoo! network. It provides financial news, data and commentary including stock quotes, press releases, financial reports, and original content. It also offers some online tools for personal finance management. In addition to posting partner content from other web sites, it posts original stories by its team of staff journalists. It is ranked 20th by Similar Web on the list of largest news and media websites.

    Description: This dataset contains financial information for companies listed on major stock exchanges around the world, as provided by Yahoo Finance. The data covers a range of industries and includes key financial metrics such as price, volume, market capitalization, P/E ratio, and more.

    ### python 1.Content: 2.Symbol: 3.Name: 4.Price: 5.Volume: 6.Market cap: 7.P/E ratio:

    The data is sourced from Yahoo Finance and is updated daily, providing users with the most up-to-date financial information for each company listed.

    The dataset is suitable for anyone interested in analyzing or predicting stock market trends and is particularly useful for financial analysts, investors, and traders.

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Click to copy link
Link copied
Close
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Damir Pozderac; Damir Pozderac; Ehlimana Cogo; Ehlimana Cogo; Irfan Prazina; Irfan Prazina; Emir Cogo; Emir Cogo; Šeila Bećirović; Šeila Bećirović; Vensada Okanovic; Vensada Okanovic (2025). Dynamic web page change content detection [Dataset]. http://doi.org/10.5281/zenodo.12699013
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Dynamic web page change content detection

Explore at:
Dataset updated
Apr 30, 2025
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Damir Pozderac; Damir Pozderac; Ehlimana Cogo; Ehlimana Cogo; Irfan Prazina; Irfan Prazina; Emir Cogo; Emir Cogo; Šeila Bećirović; Šeila Bećirović; Vensada Okanovic; Vensada Okanovic
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This dataset contains 4 parts. "SimilarWeb dataset with screenshots" is created by scraping web elements, their CSS, and corresponding screenshots in three different time intervals for around 100 web pages. Based on this data, the "SimilarWeb dataset with SSIM column" is created with the target column containing the structural similarity index measure (SSIM) of the captured screenshots. This part of the dataset is used to train machine learning regression models. To evaluate approach, "Accessible web pages dataset" and "General use web pages dataset" parts of the dataset are used.

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