Foreword

This dataset is a preview of a bigger dataset. My Telegram bot will answer your queries for more data and also allow you to contact me.

Context

When Dating apps like Tinder were becoming viral, people wanted to have the best profile in order to get more matches and more potential encounters. Unlike other previous dating platforms, those new ones emphasized on the mutuality of attraction before allowing any two people to get in touch and chat. This made it all the more important to create the best profile in order to get the best first impression.

Parallel to that, we Humans have always been in awe before charismatic and inspiring people. The more charismatic people tend to be followed and listened to by more people. Through their metrics such as the number of friends/followers, social networks give some ways of "measuring" the potential charisma of some people.

In regard to all that, one can then think: - what makes a great user profile ? - how to make the best first impression in order to get more matches (and ultimately find love, or new friendships) ? - what makes a person charismatic ? - how do charismatic people present themselves ?

In order to try and understand those different social questions, I decided to create a dataset of user profile informations using the social network Lovoo when it came out. By using different methodologies, I was able to gather user profile data, as well as some usually unavailable metrics (such as the number of profile visits).

Content

The dataset contains user profile infos of users of the website Lovoo.

The dataset was gathered during spring 2015 (april, may). At that time, Lovoo was expanding in european countries (among others), while Tinder was trending both in America and in Europe. At that time the iOS version of the Lovoo app was in version 3.

Accessory image data

The dataset references pictures (field pictureId) of user profiles. These pictures are also available for a fraction of users but have not been uploaded and should be asked separately.

The idea when gathering the profile pictures was to determine whether some correlations could be identified between a profile picture and the reputation or success of a given profile. Since first impression matters, a sound hypothesis to make is that the profile picture might have a great influence on the number of profile visits, matches and so on. Do not forget that only a fraction of a user's profile is seen when browsing through a list of users.

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Details about collection methodology

In order to gather the data, I developed a set of tools that would save the data while browsing through profiles and doing searches. Because of this approach (and the constraints that forced me to develop this approach) I could only gather user profiles that were recommended by Lovoo's algorithm for 2 profiles I created for this purpose occasion (male, open to friends & chats & dates). That is why there are only female users in the dataset. Another work could be done to fetch similar data for both genders or other age ranges.

Regarding the number of user profiles It turned out that the recommendation algorithm always seemed to output the same set of user profiles. This meant Lovoo's algorithm was probably heavily relying on settings like location (to recommend more people nearby than people in different places or countries) and maybe cookies. This diminished the number of different user profiles that would be presented and included in the dataset.

Inspiration

As mentioned in the introduction, there are a lot of questions we can answer using a dataset such as this one. Some questions are related to - popularity, charisma - census and demographic studies. - Statistics about the interest of people joining dating apps (making friends, finding someone to date, finding true love, ...). - Detecting influencers / potential influencers and studying them

Previously mentioned: - what makes a great user profile ? - how to make the best first impression in order to get more matches (and ultimately find love, or new friendships) ? - what makes a person charismatic ? - how do charismatic people present themselves ?

Other works: - A starter analysis is available on my data.world account, made using a SQL query. Another file has been created through that mean on the dataset page. - The kaggle version of the dataset might contain a starter kernel.

This research conducted an online survey to investigate the relationship between dating app use and hookup intention. It measured dating app use, perceived descriptive norms, injunctive norms, fear of negative evaluation, hookup intention, and demographic information including age, gender, sexual orientation, and relationship status.

BackgroundUniversity campus clinics provide crucial sexual health services to students, including STI/HIV screening, testing, contraception, and counseling. These clinics are essential for engaging young adults who may lack access to primary care or have difficulty reaching off-campus services. Dating apps are widely used by young adults, yet there is a lack of studies on how they affect sexual practices. This study aimed to evaluate the use of dating apps, engagement in condomless sexual activity, and the prevalence of STIs among young adult college students in Northern Texas.MethodsA cross-sectional survey was conducted from August to December 2022 among undergraduate and graduate students aged 18–35 at a large university in Northern Texas. A total of 122 eligible participants completed the survey, which assessed demographics, sexual behaviors, dating app use, and STI/HIV testing practices. Descriptive statistics, bivariate analyses, and multivariate Poisson regression analyses with robust variance were performed to identify factors associated with dating app use and condomless sexual activity.ResultsTwo-thirds of participants reported using dating apps. Significant differences were found between app users and non-users regarding demographic factors and unprotected sexual behaviors. Dating app users were more likely to report multiple sexual partners, inconsistent condom use, and a higher likelihood of engaging in unprotected sex. Poisson regression analysis indicated that app use was associated with residing in large urban areas, frequent use of campus STI/HIV screening services, and having multiple sexual partners (p 

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📊 Dataset README (Updated with Temporal Coverage) 📈 Overview 🌐 This README document provides detailed information about a dataset that combines temperature 🌡️ and rainfall 🌧️ data. The temperature data is sourced from NASA's POWER Project, and the rainfall data is obtained from the Humanitarian Data Exchange (HDX) website, specifically focusing on Bangladesh rainfall data. Temperature Data Source 🔥 Source: NASA's POWER (Prediction of Worldwide Energy Resources) Data Access Viewer URL: NASA POWER Data Access Viewer Description: The POWER Project provides solar and meteorological data sets, primarily intended for renewable energy, sustainable buildings, agriculture, and other related applications. The temperature data from this source is a part of NASA's global meteorological data. Rainfall Data Source 🌧️ Source: Humanitarian Data Exchange (HDX) URL: Bangladesh Rainfall Data - HDX Description: HDX hosts various humanitarian data including climate and weather-related datasets. The rainfall data for Bangladesh is part of their collection, providing detailed subnational rainfall statistics. Dataset Description 📝 Composition 📊 The dataset is a combination of the temperature and rainfall data, aligned by date to facilitate joint analysis. The key components are: Temperature Data (tem): Represents the monthly average temperature, presumably in degrees Celsius. Rainfall Data (rain): Indicates monthly total rainfall, presumably measured in millimeters. Structure 🏗️ The dataset is structured into a CSV file with the following columns: tem: Average temperature for the month. Month: The month for the data point, ranging from 1 (January) to 12 (December). Year: The year of the data point. rain: Total rainfall for the month. Temporal Coverage 📆 Earliest Date: 1901 Latest Date: 2023 This dataset provides a historical perspective on climate trends from the earliest year of 1901 to the most recent data available up to 2023. Usage and Applications 🚀 This dataset is particularly useful for studying climatic patterns, seasonal changes, and long-term climate trends. Applications include but are not limited to: Climatological research and climate change studies. Agricultural planning and forecasting. Environmental and ecological studies. Resource management and planning in sectors sensitive to climatic variations. Limitations and Considerations 🚧 Geographical Specificity: The rainfall data is specific to Bangladesh and may not represent global patterns. Data Integration: The temperature and rainfall data come from two different sources; users should consider potential discrepancies in data collection methods and accuracy. Updates and Maintenance 🔄 Data Update Frequency: Check the source websites for the update frequency and availability of more recent data. Last Updated: Refer to the source websites for the last update date of the data. Licensing and Usage Rights ©️ Users should refer to the respective source websites for information on licensing and usage rights. It is important to adhere to the terms and conditions set by the data providers. Contact Information 📞 For specific queries related to the temperature or rainfall data, users should contact the respective data providers through their official communication channels provided on their websites.

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