3 datasets found
  1. m

    A Sentimental Analysis Utilizing RapidMiner: Understanding the Insight of...

    • data.mendeley.com
    Updated Jun 30, 2025
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    Nabilah Ramadhanti (2025). A Sentimental Analysis Utilizing RapidMiner: Understanding the Insight of Strava's Users [Dataset]. http://doi.org/10.17632/845ms7sk3k.1
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    Unique identifier
    https://doi.org/10.17632/845ms7sk3k.1
    Dataset updated
    Jun 30, 2025
    Authors
    Nabilah Ramadhanti
    License

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

    Description

    This dataset contains user reviews of the Strava application collected from the Google Play Store. The data consists of textual reviews submitted by users, along with associated metadata such as review date, user rating (on a scale of 1 to 5), and reviewer name or alias. In some cases, the dataset may also include the number of likes each review received and the version of the app being reviewed. These reviews offer valuable insights into user experiences, satisfaction, complaints, feature requests, and perceptions of the app’s performance and usability.

  2. w

    Global Logistic Regression Models Market Research Report: By Deployment Mode...

    • wiseguyreports.com
    Updated Jul 23, 2024
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    wWiseguy Research Consultants Pvt Ltd (2024). Global Logistic Regression Models Market Research Report: By Deployment Mode (Cloud-based, On-premises), By Application (Fraud Detection, Risk Assessment, Predictive Analytics, Customer Churn Prediction, Medical Diagnosis), By Industry (Financial Services, Healthcare, Retail and eCommerce, Manufacturing, Transportation and Logistics), By Model Complexity (Simple Models, Complex Models, Deep Learning Models), By Data Type (Structured Data, Unstructured Data, Semi-structured Data) and By Regional (North America, Europe, South America, Asia Pacific, Middle East and Africa) - Forecast to 2032. [Dataset]. https://www.wiseguyreports.com/reports/logistic-regression-models-market
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    Dataset updated
    Jul 23, 2024
    Dataset authored and provided by
    wWiseguy Research Consultants Pvt Ltd
    License

    https://www.wiseguyreports.com/pages/privacy-policyhttps://www.wiseguyreports.com/pages/privacy-policy

    Time period covered
    Jan 7, 2024
    Area covered
    Global
    Description
    BASE YEAR2024
    HISTORICAL DATA2019 - 2024
    REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
    MARKET SIZE 20235.01(USD Billion)
    MARKET SIZE 20245.64(USD Billion)
    MARKET SIZE 203214.52(USD Billion)
    SEGMENTS COVEREDDeployment Mode ,Application ,Industry ,Model Complexity ,Data Type ,Regional
    COUNTRIES COVEREDNorth America, Europe, APAC, South America, MEA
    KEY MARKET DYNAMICSCloudbased Deployment Integration of Machine Learning Big Data Analytics Increase in Demand for Predictive Analytics Rising Prevalence of Chronic Diseases
    MARKET FORECAST UNITSUSD Billion
    KEY COMPANIES PROFILEDQlik Technologies ,Oracle ,Tableau Software ,Alteryx ,Teradata ,SAS Institute ,Dell Technologies ,KNIME ,H2O.ai ,DataRobot ,HP Enterprise ,SAP SE ,Microsoft ,IBM ,RapidMiner
    MARKET FORECAST PERIOD2025 - 2032
    KEY MARKET OPPORTUNITIES1 Expanding healthcare applications 2 Growing demand in pharmaceuticals 3 Rise of ecommerce and logistics 4 Increasing focus on predictive analytics 5 Advancements in machine learning algorithms
    COMPOUND ANNUAL GROWTH RATE (CAGR) 12.56% (2025 - 2032)
  3. m

    Data for: CONSTRUCTION AUTOMATION: RESEARCH AREAS, INDUSTRY CONCERNS AND...

    • data.mendeley.com
    Updated Jun 7, 2018
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    Qian Chen (2018). Data for: CONSTRUCTION AUTOMATION: RESEARCH AREAS, INDUSTRY CONCERNS AND SUGGESTIONS FOR ADVANCEMENT [Dataset]. http://doi.org/10.17632/k7zsb8r4c9.1
    Explore at:
    Unique identifier
    https://doi.org/10.17632/k7zsb8r4c9.1
    Dataset updated
    Jun 7, 2018
    Authors
    Qian Chen
    License

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

    Description

    "vos viewer text 1" and "vos viewer text 2" are files to be imported into VOS Viewer for analysis of scientific publications "web data all combined-for rapid miner" is the file to be imported into RapidMiner studio for analysis of social media related to construction automation

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Nabilah Ramadhanti (2025). A Sentimental Analysis Utilizing RapidMiner: Understanding the Insight of Strava's Users [Dataset]. http://doi.org/10.17632/845ms7sk3k.1

A Sentimental Analysis Utilizing RapidMiner: Understanding the Insight of Strava's Users

Explore at:
Unique identifier
https://doi.org/10.17632/845ms7sk3k.1
Dataset updated
Jun 30, 2025
Authors
Nabilah Ramadhanti
License

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

Description

This dataset contains user reviews of the Strava application collected from the Google Play Store. The data consists of textual reviews submitted by users, along with associated metadata such as review date, user rating (on a scale of 1 to 5), and reviewer name or alias. In some cases, the dataset may also include the number of likes each review received and the version of the app being reviewed. These reviews offer valuable insights into user experiences, satisfaction, complaints, feature requests, and perceptions of the app’s performance and usability.

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