100+ datasets found
  1. h

    email-Eu

    • huggingface.co
    Updated Apr 4, 2024
    + more versions
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    Saurav Maheshkar (2024). email-Eu [Dataset]. https://huggingface.co/datasets/SauravMaheshkar/email-Eu
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 4, 2024
    Authors
    Saurav Maheshkar
    License

    https://choosealicense.com/licenses/unknown/https://choosealicense.com/licenses/unknown/

    Description

    Source Paper: https://arxiv.org/abs/1802.06916

      Usage
    

    from torch_geometric.datasets.cornell import CornellTemporalHyperGraphDataset

    dataset = CornellTemporalHyperGraphDataset(root = "./", name="email-Eu", split="train")

      Citation
    

    @article{Benson-2018-simplicial, author = {Benson, Austin R. and Abebe, Rediet and Schaub, Michael T. and Jadbabaie, Ali and Kleinberg, Jon}, title = {Simplicial closure and higher-order link prediction}, year = {2018}, doi =… See the full description on the dataset page: https://huggingface.co/datasets/SauravMaheshkar/email-Eu.

  2. O

    Email-EU

    • opendatalab.com
    • zenodo.org
    zip
    Updated Sep 10, 2022
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    Purdue University (2022). Email-EU [Dataset]. https://opendatalab.com/OpenDataLab/Email-EU
    Explore at:
    zip(10825548 bytes)Available download formats
    Dataset updated
    Sep 10, 2022
    Dataset provided by
    Purdue University
    Stanford University
    Description

    EmailEU is a directed temporal network constructed from email exchanges in a large European research institution for a 803-day period. It contains 986 email addresses as nodes and 332,334 emails as edges with timestamps. There are 42 ground truth departments in the dataset.

  3. t

    Enron Email Network - Dataset - LDM

    • service.tib.eu
    Updated Dec 16, 2024
    + more versions
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    (2024). Enron Email Network - Dataset - LDM [Dataset]. https://service.tib.eu/ldmservice/dataset/enron-email-network
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    Dataset updated
    Dec 16, 2024
    Description

    The dataset used in the paper is the Enron email network.

  4. Top AI features in email marketing in Europe & the U.S. 2023

    • statista.com
    Updated Jun 23, 2025
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    Top AI features in email marketing in Europe & the U.S. 2023 [Dataset]. https://www.statista.com/statistics/1406421/ai-feautures-email-marketing/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    During a 2023 survey carried out among email marketers from the United States, the United Kingdom, and other European countries, it was found that automatic content and image generation was the most interesting application of artificial intelligence (AI) in email marketing, named by approximately ** percent of respondents. It was closely followed by personalization of content and newsletters, mentioned by ** percent of the interviewed.

  5. E-mail communication usage in European countries 2020

    • statista.com
    Updated Jul 5, 2021
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    Statista (2021). E-mail communication usage in European countries 2020 [Dataset]. https://www.statista.com/statistics/380552/number-of-individuals-who-send-or-receive-e-mails-in-european-countries/
    Explore at:
    Dataset updated
    Jul 5, 2021
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Europe
    Description

    This statistic shows the percentage of individuals in selected European countries who had used the internet for e-mail communication from 2017 to 2020. The share of individuals who send or received e-mails was highest in Denmark, with 96 percent of individuals using the internet in this way.

  6. T

    European Union - Individuals using the internet for sending/receiving...

    • tradingeconomics.com
    • cdn.tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 16, 2024
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    TRADING ECONOMICS (2024). European Union - Individuals using the internet for sending/receiving e-mails [Dataset]. https://tradingeconomics.com/european-union/individuals-using-the-internet-for-sending-receiving-e-mails-eurostat-data.html
    Explore at:
    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Jul 16, 2024
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    European Union
    Description

    European Union - Individuals using the internet for sending/receiving e-mails was 80.42% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for European Union - Individuals using the internet for sending/receiving e-mails - last updated from the EUROSTAT on June of 2025. Historically, European Union - Individuals using the internet for sending/receiving e-mails reached a record high of 80.42% in December of 2024 and a record low of 55.00% in December of 2009.

  7. d

    Graph theory indicators for e-mail network

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 22, 2023
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    Christidis, Panayotis (2023). Graph theory indicators for e-mail network [Dataset]. http://doi.org/10.7910/DVN/DC5M3E
    Explore at:
    Dataset updated
    Nov 22, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Christidis, Panayotis
    Description

    This dataset includes graph theory indicators (centrality and clustering coefficients) for the Stanford Network Analysis Project (SNAP) "email-Eu-core-temporal" network, a well-known reference dataset for Social Network Analysis (SNA) of e-mail traffic.

  8. B2B Email Data | EU Premium B2B Emails & Phone Numbers Dataset - APIs and...

    • data.success.ai
    Updated Oct 12, 2024
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    Success.ai (2024). B2B Email Data | EU Premium B2B Emails & Phone Numbers Dataset - APIs and flat files available – 170M+, Verified Profiles - Best Price Guarantee [Dataset]. https://data.success.ai/products/success-ai-eu-premium-b2b-emails-phone-numbers-dataset-success-ai
    Explore at:
    Dataset updated
    Oct 12, 2024
    Dataset provided by
    Area covered
    United Kingdom
    Description

    Success.ai’s EU Premium B2B Emails & Phone Numbers Dataset offers direct access to over 170 million verified B2B profiles, including key contact details across diverse industries in the United States. Available as Flat files and APIs, verified, complete, and at the Best Price on the market.

  9. B2B Email Data | EU Premium B2B Emails & Phone Numbers Dataset - APIs and...

    • datarade.ai
    Updated Oct 25, 2024
    + more versions
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    Success.ai (2024). B2B Email Data | EU Premium B2B Emails & Phone Numbers Dataset - APIs and flat files available – 170M+, Verified Profiles - Best Price Guarantee [Dataset]. https://datarade.ai/data-products/success-ai-eu-premium-b2b-emails-phone-numbers-dataset-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Oct 25, 2024
    Dataset provided by
    Area covered
    India, El Salvador, Western Sahara, Spain, Congo (Democratic Republic of the), Ukraine, Sao Tome and Principe, Wallis and Futuna, Kiribati, Malaysia
    Description

    Success.ai offers a comprehensive, enterprise-ready B2B leads data solution, ideal for businesses seeking access to over 150 million verified employee profiles and 170 million work emails. Our data empowers organizations across industries to target key decision-makers, optimize recruitment, and fuel B2B marketing efforts. Whether you're looking for UK B2B data, B2B marketing data, or global B2B contact data, Success.ai provides the insights you need with pinpoint accuracy.

    Tailored for B2B Sales, Marketing, Recruitment and more: Our B2B contact data and B2B email data solutions are designed to enhance your lead generation, sales, and recruitment efforts. Build hyper-targeted lists based on job title, industry, seniority, and geographic location. Whether you’re reaching mid-level professionals or C-suite executives, Success.ai delivers the data you need to connect with the right people.

    API Features:

    • Real-Time Updates: Our APIs deliver real-time updates, ensuring that the contact data your business relies on is always current and accurate.
    • High Volume Handling: Designed to support up to 860k API calls per day, our system is built for scalability and responsiveness, catering to enterprises of all sizes.
    • Flexible Integration: Easily integrate with CRM systems, marketing automation tools, and other enterprise applications to streamline your workflows and enhance productivity.

    Benefits of the EU Premium Dataset:

    Targeted Reach: Reach potential leads with detailed insights including email addresses, phone numbers, job titles, and more, specifically within the EU markets. Enhanced Lead Quality: Every profile is thoroughly verified, enhancing the quality of your outreach and increasing the likelihood of successful engagements. Best Price Guarantee: We are committed to providing these extensive services at the most competitive prices, ensuring that you receive the best value for your investment.

    Key Categories Served: B2B sales leads – Identify decision-makers in key industries, B2B marketing data – Target professionals for your marketing campaigns, Recruitment data – Source top talent efficiently and reduce hiring times, CRM enrichment – Update and enhance your CRM with verified, updated data, Global reach – Coverage across 195 countries, including the United States, United Kingdom, Germany, India, Singapore, and more.

    Global Coverage with Real-Time Accuracy: Success.ai’s dataset spans a wide range of industries such as technology, finance, healthcare, and manufacturing. With continuous real-time updates, your team can rely on the most accurate data available: 150M+ Employee Profiles: Access professional profiles worldwide with insights including full name, job title, seniority, and industry. 170M Verified Work Emails: Reach decision-makers directly with verified work emails, available across industries and geographies, including Singapore and UK B2B data. GDPR-Compliant: Our data is fully compliant with GDPR and other global privacy regulations, ensuring safe and legal use of B2B marketing data.

    Key Data Points for Every Employee Profile: Every profile in Success.ai’s database includes over 20 critical data points, providing the information needed to power B2B sales and marketing campaigns: Full Name, Job Title, Company, Work Email, Location, Phone Number, LinkedIn Profile, Experience, Education, Technographic Data, Languages, Certifications, Industry, Publications & Awards.

    Use Cases Across Industries: Success.ai’s B2B data solution is incredibly versatile and can support various enterprise use cases, including: B2B Marketing Campaigns: Reach high-value professionals in industries such as technology, finance, and healthcare. Enterprise Sales Outreach: Build targeted B2B contact lists to improve sales efforts and increase conversions. Talent Acquisition: Accelerate hiring by sourcing top talent with accurate and updated employee data, filtered by job title, industry, and location. Market Research: Gain insights into employment trends and company profiles to enrich market research. CRM Data Enrichment: Ensure your CRM stays accurate by integrating updated B2B contact data. Event Targeting: Create lists for webinars, conferences, and product launches by targeting professionals in key industries.

    Use Cases for Success.ai's Contact Data - Targeted B2B Marketing: Create precise campaigns by targeting key professionals in industries like tech and finance. - Sales Outreach: Build focused sales lists of decision-makers and C-suite executives for faster deal cycles. - Recruiting Top Talent: Easily find and hire qualified professionals with updated employee profiles. - CRM Enrichment: Keep your CRM current with verified, accurate employee data. - Event Targeting: Create attendee lists for events by targeting relevant professionals in key sectors. - Market Research: Gain insights into employment trends and company profiles for better business decisions. - Executive Search: So...

  10. c

    Europe Email Marketing Software Market Report 2025, Market Size, Share,...

    • cognitivemarketresearch.com
    pdf,excel,csv,ppt
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    Cognitive Market Research, Europe Email Marketing Software Market Report 2025, Market Size, Share, Growth, CAGR, Forecast, Revenue [Dataset]. https://www.cognitivemarketresearch.com/regional-analysis/europe-email-marketing-software-market-report
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset authored and provided by
    Cognitive Market Research
    License

    https://www.cognitivemarketresearch.com/privacy-policyhttps://www.cognitivemarketresearch.com/privacy-policy

    Time period covered
    2021 - 2033
    Area covered
    Europe, Region
    Description

    Access Europe Email Marketing Software Industry Overview which includes Europe country analysis of (United Kingdom, France, Germany, Italy, Russia, Spain, Sweden, Denmark, Switzerland, Luxembourg, Rest of Europe), market split by Industry, Application, Channel, Deployment, Enterprise

  11. o

    Enron Email Time-Series Network

    • explore.openaire.eu
    • zenodo.org
    Updated Aug 9, 2018
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    Volodymyr Miz; Benjamin Ricaud; Pierre Vandergheynst (2018). Enron Email Time-Series Network [Dataset]. http://doi.org/10.5281/zenodo.1342352
    Explore at:
    Dataset updated
    Aug 9, 2018
    Authors
    Volodymyr Miz; Benjamin Ricaud; Pierre Vandergheynst
    Description

    We use the Enron email dataset to build a network of email addresses. It contains 614586 emails sent over the period from 6 January 1998 until 4 February 2004. During the pre-processing, we remove the periods of low activity and keep the emails from 1 January 1999 until 31 July 2002 which is 1448 days of email records in total. Also, we remove email addresses that sent less than three emails over that period. In total, the Enron email network contains 6 600 nodes and 50 897 edges. To build a graph G = (V, E), we use email addresses as nodes V. Every node vi has an attribute which is a time-varying signal that corresponds to the number of emails sent from this address during a day. We draw an edge eij between two nodes i and j if there is at least one email exchange between the corresponding addresses. Column 'Count' in 'edges.csv' file is the number of 'From'->'To' email exchanges between the two addresses. This column can be used as an edge weight. The file 'nodes.csv' contains a dictionary that is a compressed representation of time-series. The format of the dictionary is Day->The Number Of Emails Sent By the Address During That Day. The total number of days is 1448. 'id-email.csv' is a file containing the actual email addresses.

  12. Frequency of experiences of social media or email accounts being hacked EU...

    • statista.com
    Updated Jul 18, 2025
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    Frequency of experiences of social media or email accounts being hacked EU 2019 [Dataset]. https://www.statista.com/statistics/1089964/frequency-of-experiences-of-social-media-or-email-accounts-being-hacked-in-the-eu/
    Explore at:
    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2019 - Nov 2019
    Area covered
    European Union
    Description

    This statistic displays the findings of a survey on the frequency of experiences of social media or email accounts being hacked in the European Union (EU) as of 2019. During the survey period, it was found that ** percent of respondents reported that they experienced such situations at least once.

  13. Email Address Data | IT Companies in Europe | Verified Business Profiles &...

    • data.success.ai
    Updated Dec 13, 2024
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    Success.ai (2024). Email Address Data | IT Companies in Europe | Verified Business Profiles & Contacts - Unbeatable Price [Dataset]. https://data.success.ai/products/email-address-data-it-companies-in-europe-verified-busine-success-ai
    Explore at:
    Dataset updated
    Dec 13, 2024
    Dataset provided by
    Area covered
    Slovenia, Finland, Switzerland, San Marino, Spain, Poland, Austria, Bulgaria, Kosovo, Greece, Europe
    Description

    Access Email Address Data for IT businesses across Europe with Success.ai. Includes verified work emails, firmographic data, and employee counts. Continuously updated datasets. Best price guaranteed.

  14. Communication Graphs

    • kaggle.com
    Updated Nov 15, 2021
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    Subhajit Sahu (2021). Communication Graphs [Dataset]. https://www.kaggle.com/wolfram77/graphs-communication/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 15, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Subhajit Sahu
    License

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

    Description

    email-EuAll: EU email communication network

    The network was generated using email data from a large European research institution. For a period from October 2003 to May 2005 (18 months) we have anonymized information about all incoming and outgoing email of the research institution. For each sent or received email message we know the time, the sender and the recipient of the email. Overall we have 3,038,531 emails between 287,755 different email addresses. Note that we have a complete email graph for only 1,258 email addresses that come from the research institution. Furthermore, there are 34,203 email addresses that both sent and received email within the span of our dataset. All other email addresses are either non-existing, mistyped or spam.

    Given a set of email messages, each node corresponds to an email address. We create a directed edge between nodes i and j, if i sent at least one message to j.

    email-Enron: Enron email network

    Enron email communication network covers all the email communication within a dataset of around half million emails. This data was originally made public, and posted to the web, by the Federal Energy Regulatory Commission during its investigation. Nodes of the network are email addresses and if an address i sent at least one email to address j, the graph contains an undirected edge from i to j. Note that non-Enron email addresses act as sinks and sources in the network as we only observe their communication with the Enron email addresses.

    The Enron email data was originally released by William Cohen at CMU.

    wiki-Talk: Wikipedia Talk network

    Wikipedia is a free encyclopedia written collaboratively by volunteers around the world. Each registered user has a talk page, that she and other users can edit in order to communicate and discuss updates to various articles on Wikipedia. Using the latest complete dump of Wikipedia page edit history (from January 3 2008) we extracted all user talk page changes and created a network.

    The network contains all the users and discussion from the inception of Wikipedia till January 2008. Nodes in the network represent Wikipedia users and a directed edge from node i to node j represents that user i at least once edited a talk page of user j.

    comm-f2f-Resistance: Dynamic Face-to-Face Interaction Networks

    The dynamic face-to-face interaction networks represent the interactions that happen during discussions between a group of participants playing the Resistance game. This dataset contains networks extracted from 62 games. Each game is played by 5-8 participants and lasts between 45--60 minutes. We extract dynamically evolving networks from the free-form discussions using the ICAF algorithm. The extracted networks are used to characterize and detect group deceptive behavior using the DeceptionRank algorithm.

    The networks are weighted, directed and temporal. Each node represents a participant. At each 1/3 second, a directed edge from node u to v is weighted by the probability of participant u looking at participant v or the laptop. Additionally, we also provide a binary version where an edge from u to v indicates participant u looks at participant v (or the laptop).

    Stanford Network Analysis Platform (SNAP) is a general purpose, high performance system for analysis and manipulation of large networks. Graphs consists of nodes and directed/undirected/multiple edges between the graph nodes. Networks are graphs with data on nodes and/or edges of the network.

    The core SNAP library is written in C++ and optimized for maximum performance and compact graph representation. It easily scales to massive networks with hundreds of millions of nodes, and billions of edges. It efficiently manipulates large graphs, calculates structural properties, generates regular and random graphs, and supports attributes on nodes and edges. Besides scalability to large graphs, an additional strength of SNAP is that nodes, edges and attributes in a graph or a network can be changed dynamically during the computation.

    SNAP was originally developed by Jure Leskovec in the course of his PhD studies. The first release was made available in Nov, 2009. SNAP uses a general purpose STL (Standard Template Library)-like library GLib developed at Jozef Stefan Institute. SNAP and GLib are being actively developed and used in numerous academic and industrial projects.

    http://snap.stanford.edu/data/index.html#email

  15. Effectiveness of AI in email marketing in Europe & the U.S. 2023

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Effectiveness of AI in email marketing in Europe & the U.S. 2023 [Dataset]. https://www.statista.com/statistics/1406430/ai-effectiveness-email-marketing/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States, United Kingdom
    Description

    During a 2023 survey carried out among email marketers from the United States, the United Kingdom, and other European countries, it was found that approximately ** percent of respondents believed that AI-supported email marketing was more effective than traditional email marketing approaches. Roughly ***percent noticed no significant difference or said they believed it was as effective as traditional approaches.

  16. B2B Email Data | European Professionals | Access Verified Profiles with...

    • datarade.ai
    Updated Jan 1, 2018
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    Success.ai (2018). B2B Email Data | European Professionals | Access Verified Profiles with Email Addresses & Contact Info from 700M+ Dataset | Best Price Guarantee [Dataset]. https://datarade.ai/data-products/b2b-email-data-european-professionals-access-verified-pro-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jan 1, 2018
    Dataset provided by
    Area covered
    Denmark, Spain, Sweden, Andorra, Romania, Greece, Italy, Hungary, Croatia, Germany
    Description

    Success.ai's B2B Email Data for European Professionals offers unprecedented access to a vast dataset of over 700 million verified profiles, meticulously curated to empower your marketing and sales strategies across Europe. This comprehensive database includes work emails, phone numbers, and extensive professional histories, providing the key details you need to connect with decision-makers and influencers in various industries.

    Why Choose Success.ai’s B2B Email Data?

    Extensive European Coverage: Our dataset spans across the entire European continent, including both EU and non-EU countries, ensuring you can reach professionals in key markets. Verified Contact Details: Each profile is thoroughly verified for accuracy, ensuring you have the most reliable emails and contact numbers at your fingertips. In-depth Professional Histories: Gain insights into the careers of potential leads, including their past roles, industries of expertise, and professional achievements. Data Features:

    Work Emails and Phone Numbers: Direct communication channels to engage with prospects effectively. Professional Backgrounds: Detailed histories to help you tailor your outreach and personalize communication. Industry and Role Segmentation: Data segmented by industry and job role to refine your targeting and increase conversion rates. Flexible Delivery and Integration: Our data can be delivered in various formats such as CSV, Excel, or through an API, allowing for easy integration into your existing CRM systems or marketing platforms. This flexibility ensures that you can start leveraging the data quickly, with minimal setup time required.

    Competitive Pricing with Best Price Guarantee: We are committed to providing you the best value for your investment. Our Best Price Guarantee ensures you receive the highest quality data at the most competitive rates in the market.

    Targeted Applications for B2B Email Data:

    Lead Generation: Identify and connect with potential clients by utilizing accurate contact data to support cold emailing and telemarketing efforts. Account-Based Marketing (ABM): Enhance your ABM campaigns by reaching the key stakeholders in target companies directly. Market Research: Use detailed professional backgrounds to analyze market trends and understand the competitive landscape. Event Promotion: Drive attendance to webinars, conferences, and trade shows by reaching out to relevant professionals. Quality Assurance and Compliance:

    Data Accuracy: Our stringent verification processes ensure a high level of accuracy, with regular updates to keep the data fresh. Compliance with Data Protection Laws: All data is collected and processed in compliance with GDPR and other relevant legislation, ensuring lawful and ethical use. Support and Consultation:

    Customer Support: Our dedicated support team is available to assist with any queries or issues you may encounter. Consultation Services: Benefit from our expertise in data-driven marketing and sales strategies through personalized consultation sessions. Get Started with Success.ai Today: Empower your business with Success.ai’s B2B Email Data for European Professionals and start building meaningful connections that drive growth. Contact us to explore our data solutions and discover how we can help you achieve your business objectives.

  17. Communities Graphs

    • kaggle.com
    Updated Nov 15, 2021
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    Subhajit Sahu (2021). Communities Graphs [Dataset]. https://www.kaggle.com/datasets/wolfram77/graphs-communities/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 15, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Subhajit Sahu
    License

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

    Description

    com-LiveJournal: LiveJournal social network and ground-truth communities

    LiveJournal is a free on-line blogging community where users declare friendship each other. LiveJournal also allows users form a group which other members can then join. We consider such user-defined groups as ground-truth communities. We provide the LiveJournal friendship social network and ground-truth communities.

    We regard each connected component in a group as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

    com-Friendster: Friendster social network and ground-truth communities

    Friendster is an on-line gaming network. Before re-launching as a game website, Friendster was a social networking site where users can form friendship edge each other. Friendster social network also allows users form a group which other members can then join. We consider such user-defined groups as ground-truth communities. For the social network, we take the induced subgraph of the nodes that either belong to at least one community or are connected to other nodes that belong to at least one community. This data is provided by The Web Archive Project, where the full graph is available.

    We regard each connected component in a group as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

    com-Orkut: Orkut social network and ground-truth communities

    Orkut is a free on-line social network where users form friendship each other. Orkut also allows users form a group which other members can then join. We consider such user-defined groups as ground-truth communities. We provide the Orkut friendship social network and ground-truth communities. This data is provided by Alan Mislove et al.

    We regard each connected component in a group as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

    com-Youtube: Youtube social network and ground-truth communities

    Youtube is a video-sharing web site that includes a social network. In the Youtube social network, users form friendship each other and users can create groups which other users can join. We consider such user-defined groups as ground-truth communities. This data is provided by Alan Mislove et al.

    We regard each connected component in a group as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

    com-DBLP: DBLP collaboration network and ground-truth communities

    The DBLP computer science bibliography provides a comprehensive list of research papers in computer science. We construct a co-authorship network where two authors are connected if they publish at least one paper together. Publication venue, e.g, journal or conference, defines an individual ground-truth community; authors who published to a certain journal or conference form a community.

    We regard each connected component in a group as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

    com-Amazon: Amazon product co-purchasing network and ground-truth communities

    Network was collected by crawling Amazon website. It is based on Customers Who Bought This Item Also Bought feature of the Amazon website. If a product i is frequently co-purchased with product j, the graph contains an undirected edge from i to j. Each product category provided by Amazon defines each ground-truth community.

    We regard each connected component in a product category as a separate ground-truth community. We remove the ground-truth communities which have less than 3 nodes. We also provide the top 5,000 communities with highest quality which are described in our paper. As for the network, we provide the largest connected component.

    email-Eu-core: email-Eu-core network

    The network was generated using email data from a large European research institution. We have anonymized information about all incoming and outgoing email between members of the research institution. Th...

  18. T

    Euro Area - Individuals using the internet for sending/receiving e-mails

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Sep 15, 2020
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    TRADING ECONOMICS (2020). Euro Area - Individuals using the internet for sending/receiving e-mails [Dataset]. https://tradingeconomics.com/euro-area/individuals-using-the-internet-for-sending-receiving-e-mails-eurostat-data.html
    Explore at:
    excel, json, csv, xmlAvailable download formats
    Dataset updated
    Sep 15, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Euro Area
    Description

    Euro Area - Individuals using the internet for sending/receiving e-mails was 79.60% in December of 2022, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Euro Area - Individuals using the internet for sending/receiving e-mails - last updated from the EUROSTAT on June of 2025. Historically, Euro Area - Individuals using the internet for sending/receiving e-mails reached a record high of 79.60% in December of 2022 and a record low of 58.00% in December of 2009.

  19. Checking work messages and emails while on vacation in Europe 2018

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). Checking work messages and emails while on vacation in Europe 2018 [Dataset]. https://www.statista.com/statistics/912446/checking-work-messages-and-emails-on-holiday-europe/
    Explore at:
    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 22, 2018 - Jul 6, 2018
    Area covered
    Europe
    Description

    This statistic illustrates the results of a survey on checking work messages and emails while on holiday, in selected European countries in 2018. According to the study published by Ipsos, ** percent of Germans agreed that they never check for messages/emails back at their work when they go on vacation. Those in Russia and Serbia were more likely to check their messages, with only ** percent and ** percent of respondents saying they don't, respectively.

  20. T

    France - Individuals using the internet for sending/receiving e-mails

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Sep 2, 2021
    Share
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    TRADING ECONOMICS (2021). France - Individuals using the internet for sending/receiving e-mails [Dataset]. https://tradingeconomics.com/france/individuals-using-the-internet-for-sending-receiving-e-mails-eurostat-data.html
    Explore at:
    csv, excel, json, xmlAvailable download formats
    Dataset updated
    Sep 2, 2021
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    France
    Description

    France - Individuals using the internet for sending/receiving e-mails was 86.83% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for France - Individuals using the internet for sending/receiving e-mails - last updated from the EUROSTAT on July of 2025. Historically, France - Individuals using the internet for sending/receiving e-mails reached a record high of 86.83% in December of 2024 and a record low of 62.00% in December of 2009.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Saurav Maheshkar (2024). email-Eu [Dataset]. https://huggingface.co/datasets/SauravMaheshkar/email-Eu

email-Eu

SauravMaheshkar/email-Eu

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Apr 4, 2024
Authors
Saurav Maheshkar
License

https://choosealicense.com/licenses/unknown/https://choosealicense.com/licenses/unknown/

Description

Source Paper: https://arxiv.org/abs/1802.06916

  Usage

from torch_geometric.datasets.cornell import CornellTemporalHyperGraphDataset

dataset = CornellTemporalHyperGraphDataset(root = "./", name="email-Eu", split="train")

  Citation

@article{Benson-2018-simplicial, author = {Benson, Austin R. and Abebe, Rediet and Schaub, Michael T. and Jadbabaie, Ali and Kleinberg, Jon}, title = {Simplicial closure and higher-order link prediction}, year = {2018}, doi =… See the full description on the dataset page: https://huggingface.co/datasets/SauravMaheshkar/email-Eu.

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