Link to github repo: https://github.com/Ashley-Xu/AIPIFinalDataset

The dataset is intended for research, analysis, and innovation. All efforts have been made to anonymize the data to ensure that no individual can be identified or harmed by its use.

Every effort has been made to uphold the privacy and confidentiality of the individuals whose data is represented in the dataset.

The dataset may only be used for ethical, responsible, and non-exploitative purposes. Users of the dataset are expected to:

Avoid any attempt to re-identify individuals or misuse the data in ways that could lead to harm, discrimination, or stigmatization. Adhere to applicable laws, regulations, and ethical guidelines relevant to data usage and research in their jurisdiction. Cite the dataset responsibly in any derivative work to maintain transparency about its source and limitations.

The dataset may reflect biases inherent in the original data source and population. Researchers are encouraged to be aware of these limitations and to take steps to address or acknowledge biases in their work to prevent misleading conclusions or harmful applications.

While every effort has been made to anonymize the data and protect privacy, no anonymization process is entirely risk-free. Users of the dataset assume full responsibility for ensuring that their research complies with ethical and legal standards.

The data was collected from https://www.swipestats.io/ with appropriate permissions from the owner of the website.

Open source license Community Data License Agreement – Sharing – Version 1.0

According to a survey conducted in March 2025, approximately one in five Tinder users in the United States considered themselves as being a part of the LGBTQ+ community. Overall, 80 percent of users did not identify as part of the community, and three percent did not say.

Problem Statement Tinder is a casual dating site that allows users to make split-second decisions to determine if they like a potential match. The user swipes right on the profile to match the potential suitor. If the potential suitor also swipes right, a match is made and both parties are alerted.

Tinder is a massive phenomenon in the online dating world. Because of its vast user base, it potentially offers lots of data that is exciting to analyze.

We have collected a small dataset which explains the match rate of the individuals from different universities, and whether the app has helped them find a relationship.

About the Data The dataset contains information about the match rate of the individuals from different universities, and whether the app (i.e. Tinder) has helped them find a relationship.

Data Description ID : User id Segment type : Medium of Usage Segment Description : Name of Universities Answer : Do you use tinder ? Count : Number of Matches Percentage : % of matches (the value ranges from 0 to 1 as it is not multiplied with 100) It became a relationship : Success of relationship (Target)

Traffic analytics, rankings, and competitive metrics for tinder.com as of September 2025

In 2024, 'Better in person' was the leading type of communication style on Tinder in the United States, followed by 'Big time texter' and 'Bad texter'. Launched in 2012, Tinder is the most popular dating app worldwide.

Reddit: /r/Tinder

Examining User Behaviors and Attitudes

By Reddit [source]

About this dataset

This dataset provides an in-depth exploration of the world of online dating, based on data mined from Reddit's Tinder subreddit. Through analysis of the six columns titled title, score, id, url, comms_num and created (which include information such as social norms and user behaviors related to online dating), this dataset can teach us valuable insights into how people are engaging with digital media and their attitudes towards it. Unveiling potential dangers such as safety risks and scams that can arise from online dating activities is also possible with this data. Its findings are paramount for anyone interested in understanding how relationships develop on a digital platform – both for researchers uncovering the sociotechnical aspects of online dating behavior and for companies seeking further insight into their user's perspectives. All in all, this dataset might just hold all the missing pieces to understanding our current relationship dynamic!

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How to use the dataset

This dataset provides a comprehensive overview of online dating trends and behaviors observed on Reddit's Tinder subreddit. This data can be used to analyze user opinions, investigate user experiences, and discover online dating trends. To utilize this dataset effectively, there are several steps an individual can take to gain insights from the data:

Research Ideas

• Using the dataset to examine how online dating trends vary geographically and by demographics (gender, age, race etc.)
• Analyzing the language used in posts for insights into user attitudes towards online dating.
• Creating a machine learning model to predict a post's score based on its title, body and other features of the data set can help digital media companies better target their marketing efforts towards more successful posts on Tinder subreddits

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: Tinder.csv | Column name | Description | |:--------------|:--------------------------------------------------------| | title | The title of the post. (String) | | score | The number of upvotes the post has received. (Integer) | | url | The URL of the post. (String) | | comms_num | The number of comments the post has received. (Integer) | | created | The date and time the post was created. (DateTime) | | body | The body of the post. (String) | | timestamp | The timestamp of the post. (Integer) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Reddit.

The European online dating market, a dynamic sector characterized by diverse platforms and evolving user preferences, is poised for continued growth. Driven by increasing smartphone penetration, changing societal attitudes towards online relationships, and the convenience offered by digital platforms, the market is projected to expand significantly over the forecast period (2025-2033). While the exact market size for 2025 is not provided, considering a 5.20% CAGR from a hypothetical 2019 base of €2 billion (a reasonable assumption given the global scale of the online dating market), the 2025 market size can be estimated to be around €2.6 billion. The market is segmented into paying and non-paying online dating services, with paying services commanding a premium price point and offering enhanced features like profile boosts and advanced search filters. Competition is fierce, with established players like Tinder, Bumble, and Match Group Inc vying for market share alongside smaller niche platforms catering to specific demographics or relationship goals. Growth will be further fueled by innovative features, personalized matchmaking algorithms, and increased focus on safety and security measures within the apps. Regional variations are expected within Europe; the UK, Germany, and France are likely to remain dominant markets, driven by higher internet penetration and disposable income. However, growth potential is also considerable in other European countries as online dating adoption continues to increase. The key restraints to growth involve concerns around data privacy and security, the prevalence of fake profiles, and the potential for catfishing or scams. Moreover, evolving user expectations demand consistent innovation and improvement in features to keep the user experience engaging. Addressing these challenges through robust verification processes, improved user reporting mechanisms, and transparency regarding data handling will be crucial for sustained market expansion. The emergence of niche dating apps targeting specific communities or interests adds complexity and intensifies competition, further shaping the market landscape. Overall, the European online dating market displays resilience and high potential for growth, but sustained success requires a commitment to user safety, innovation, and adaptation to evolving consumer preferences. Recent developments include: February 2022 - Bumble Inc announced the acquisition of Fruitz, one of Europe's fastest-growing dating apps. The dating app is popular with Gen Z, a growing segment of online dating consumers. Such acquisitions by the major players in the region are promoting the growth of inline dating app services.. Key drivers for this market are: Continuous Innovation in Service Offerings, Growing Penetration of Smartphones and Mobile Devices. Potential restraints include: Continuous Innovation in Service Offerings, Growing Penetration of Smartphones and Mobile Devices. Notable trends are: Non Paying Online Dating to Show Significant Growth.

I've been using Tinder for quite some time now. Sometimes it led to great matches, but more often than not, it was a bit of a swipe-left experience. After a while, I started noticing some interesting patterns in the profiles I came across — particularly in their interests and how much effort was put into filling out the various sections. This curiosity sparked an idea for a personal project: analyzing Tinder profiles for a Data Analytics case study. And yes, I'm hilarious at parties (hence the Tinder usage).

Find out more in my case study

Discover the booming online dating market! Explore key trends, leading companies (Tinder, Bumble, Badoo), and regional growth projections (North America, Europe, Asia) in this comprehensive analysis. Learn about the market's impressive CAGR and future potential. Recent developments include: February 2022 - Tinder is expanding its portfolio of features by introducing blind dates as it features a popular suite of Fast Chat designed to help members connect faster through fun, innovative prompts, and games., December 2021 - Bumble has introduced a new profile design and revamped the matchmaking algorithm, where users on the dating app can have access to view a person's bio, including interests below their first picture, to get an idea about the potential match right from the beginning.. Key drivers for this market are: Increased Smartphone Penetration, As marriage agreements on matrimonial websites increase, the demand for matchmaking services.. Potential restraints include: Rising fake accounts is set to create hurdles for the Online Dating Services Market.. Notable trends are: Increased Smartphone Penetration has Boosted the Download of Online Dating Apps.

The global marriage and dating app market, currently valued at $775 million in 2025, is projected to experience robust growth, driven by increasing smartphone penetration, evolving social norms around relationships, and the convenience offered by digital platforms. The market's Compound Annual Growth Rate (CAGR) of 11.7% from 2019 to 2024 suggests a strong trajectory that is likely to continue over the forecast period (2025-2033). Key drivers include the rising popularity of online dating among younger generations, the integration of advanced features like AI-powered matching algorithms and video calling, and a growing acceptance of online relationship formation across demographics. While data privacy concerns and the potential for scams represent some restraints, the market's inherent resilience and the continuous innovation within the sector suggest these challenges will be mitigated through improved security measures and user education. The market is segmented by app type (niche dating apps, general dating apps, marriage-focused apps), user demographics (age, gender, location), and revenue models (subscription-based, freemium, advertising). Leading players like Tinder, Bumble, and Match Group are constantly expanding their features and acquiring smaller competitors to maintain their market share in a competitive landscape. The increasing use of location-based services and social media integration further fuels market growth by expanding user reach and engagement. The forecast period (2025-2033) anticipates sustained growth, driven by ongoing technological advancements, strategic partnerships, and aggressive marketing strategies employed by major players. International expansion into emerging markets with high internet and smartphone penetration represents a significant opportunity for growth. Furthermore, the increasing integration of augmented and virtual reality technologies into dating apps offers potential for enhanced user experience and engagement. The market's segmentation will likely become more nuanced, with specialized apps catering to specific niches and preferences, including those focused on long-term relationships and marriage. Competition will remain fierce, requiring companies to continuously innovate and adapt to changing user expectations to secure and maintain a competitive edge.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13364933%2F23694fae55e2e76299358693ba6f32b9%2Flv-share.jpg?generation=1684843825246772&alt=media" alt=""> ➡️ There are total 3 datasets containing valuable information. ➡️ Understand people's fame and behavior's on a dating app platform. | Column Name | Description | |---------------------|------------------------------| | Age | The age of the user. | | Number of Users | The total number of users. | | Percent Want Chats | Percentage of users who want chats. | | Percent Want Friends| Percentage of users who want friendships. | | Percent Want Dates | Percentage of users who want romantic dates. | | Mean Kisses Received| Average number of kisses received by users. | | Mean Visits Received| Average number of profile visits received by users. | | Mean Followers | Average number of followers for each user. | | Mean Languages Known| Average number of languages known by users. | | Total Want Chats | Total count of users interested in chats. | | Total Want Friends | Total count of users looking for friendships. | | Total Want Dates | Total count of users seeking romantic dates. | | Total Kisses Received| Overall count of kisses received by users. | | Total Visits Received| Overall count of profile visits received by users. | | Total Followers | Overall count of followers for all users. | | Total Languages Spoken| Total count of languages spoken by all users. |

SUMMARY

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.

https://s1.dmcdn.net/v/BnWkG1M7WuJDq2PKP/x480

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 pr...

The online dating software market is experiencing robust growth, driven by increasing smartphone penetration, evolving social norms around online dating, and the continuous innovation within dating app features. The market, estimated at $5 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This expansion is fueled by several key factors. The rise of subscription-based models, offering tiered access to premium features, is a major contributor to revenue growth. Furthermore, the diversification of dating applications catering to niche interests (e.g., faith-based dating, LGBTQ+ dating) is expanding the overall addressable market. Geographic expansion, particularly in developing economies with rapidly increasing internet usage, presents significant untapped potential. Competition remains fierce, with established players like Match Group and Bumble vying for market share alongside a robust number of specialized niche dating apps. Challenges include maintaining user engagement in an increasingly saturated market and addressing concerns regarding data privacy and security. The segmentation of the online dating software market reveals key trends. While subscription models (annual, quarterly, monthly, weekly) contribute significantly to revenue, free applications with in-app purchases are also prevalent. Application-wise, matchmaking services retain a strong foothold, although social dating and adult dating segments demonstrate rapid growth, reflecting evolving user preferences and market demands. North America and Europe currently hold the largest market shares, driven by high internet penetration and adoption rates. However, the Asia-Pacific region is poised for substantial growth over the forecast period, fueled by a burgeoning young, tech-savvy population and increasing smartphone adoption. The market faces regulatory hurdles in certain regions, concerning data protection and user safety, which presents both a challenge and an opportunity for companies prioritizing ethical practices and transparent data handling.

According to a January 2022 analysis of the leading dating apps downloaded from the Apple App Store, the Badoo mobile app was indexed as collecting the largest number of data types from its users' activity. Bumble and HER ranked second, with an index value of close to **, respectively. Grindr had a reported index value of **, while market leader Tinder was indexed with a value of ****.

Indonesia's booming e-services market is projected to reach $2.135 billion by 2033, fueled by strong growth in online education, gambling, event ticketing, and dating. Discover key trends, market drivers, and leading companies shaping this dynamic sector. Recent developments include: December 2023: PT Pelayaran Nasional Indonesia is enhancing the ease of purchasing ship tickets online by integrating this service into the Lifestyle feature within its digital ecosystem on BCA mobile. The consent of the MKP traffic intelligence system facilitates this improvement. With millions of users on the BCA mobile, consumers can now directly and effortlessly buy tickets and make payments at their convenience, anywhere and anytime. PT Mitra Kasih Perkasa, also known as MKP, consistently achieved innovative breakthroughs, encompassing ticket issuance, validation, and payment, as well as on-site and online ticket distribution and data analytics in Indonesia., March 2023: As part of the events to mark the 300th anniversary of St Petersburg University, the Petrovsky Hall hosted the signing ceremony of a Memorandum of Understanding between St Petersburg University and the Indonesia Cyber Education Institute (ICE Institute). The purposes of the agreement include the development of joint research projects in online learning, the organization of academic and scientific events that promote online learning, and the exchange of online courses for educational purposes.. Key drivers for this market are: Rise in Accessibility through Application Platforms. Potential restraints include: Rise in Accessibility through Application Platforms. Notable trends are: Online Education is Expected to Hold Significant Market Share.

The Indonesian e-services market, valued at $1.58 billion in 2025, exhibits robust growth potential, projected to expand at a compound annual growth rate (CAGR) of 3.87% from 2025 to 2033. This expansion is fueled by several key factors. Increasing internet and smartphone penetration across Indonesia's vast population is a major driver, enabling broader access to online services. Furthermore, a burgeoning young and tech-savvy population readily adopts digital solutions for education, entertainment, and daily transactions. The government's push for digitalization and initiatives to improve digital infrastructure further accelerate market growth. The rise of mobile payment systems and increased trust in online platforms contribute significantly to this positive trend. Competitive pressures among established and emerging players also stimulate innovation and enhance service offerings. While challenges remain, such as digital literacy gaps in certain segments of the population and concerns about data security and privacy, the overall outlook for the Indonesian e-services market remains exceptionally promising. Specific segments within the e-services sector display varying growth trajectories. Online education, driven by the rising demand for accessible and affordable learning resources, is expected to witness significant expansion. Similarly, online dating services are experiencing notable growth, reflecting changing social dynamics and increased comfort with online interactions. The online event ticketing sector, while dependent on broader economic conditions and public health measures, is projected to show steady growth as in-person events resume and the ease of online ticket purchasing becomes increasingly preferred. The online gambling segment, while potentially lucrative, faces regulatory hurdles and ethical concerns that may influence its growth trajectory. The competitive landscape is dynamic, with established international players alongside rapidly growing local companies vying for market share. This competition fosters innovation, improves service quality, and drives down prices, ultimately benefiting Indonesian consumers. Indonesia E-Services Market: A Comprehensive Report (2019-2033) This comprehensive report provides an in-depth analysis of the burgeoning Indonesia e-services market, covering the period from 2019 to 2033. It leverages a robust methodology, incorporating historical data (2019-2024), a base year of 2025, and forecasts extending to 2033. The report delves into key segments like online education, online gambling, online event ticketing, and online dating services, offering valuable insights for investors, businesses, and policymakers seeking to understand this dynamic market. Key market players such as Ruangguru, HarukaEdu, IndonesiaX, and others are profiled, providing competitive landscapes and future projections. Recent developments include: December 2023: PT Pelayaran Nasional Indonesia is enhancing the ease of purchasing ship tickets online by integrating this service into the Lifestyle feature within its digital ecosystem on BCA mobile. The consent of the MKP traffic intelligence system facilitates this improvement. With millions of users on the BCA mobile, consumers can now directly and effortlessly buy tickets and make payments at their convenience, anywhere and anytime. PT Mitra Kasih Perkasa, also known as MKP, consistently achieved innovative breakthroughs, encompassing ticket issuance, validation, and payment, as well as on-site and online ticket distribution and data analytics in Indonesia., March 2023: As part of the events to mark the 300th anniversary of St Petersburg University, the Petrovsky Hall hosted the signing ceremony of a Memorandum of Understanding between St Petersburg University and the Indonesia Cyber Education Institute (ICE Institute). The purposes of the agreement include the development of joint research projects in online learning, the organization of academic and scientific events that promote online learning, and the exchange of online courses for educational purposes.. Key drivers for this market are: Rise in Accessibility through Application Platforms. Potential restraints include: Rise in Accessibility through Application Platforms. Notable trends are: Online Education is Expected to Hold Significant Market Share.

The global Gay Dating App market is poised for significant expansion, driven by increasing social acceptance, a growing digital-first generation, and the continuous evolution of app functionalities catering to diverse LGBTQ+ community needs. With a robust estimated market size of $2,500 million in 2025, and a projected Compound Annual Growth Rate (CAGR) of 18% through 2033, this sector is a dynamic and lucrative segment within the broader online dating industry. The market's growth is fueled by several key drivers: the democratization of digital platforms for connection, a heightened awareness and advocacy for LGBTQ+ rights globally, and the development of more sophisticated matching algorithms and community-building features within apps. Furthermore, the increasing smartphone penetration across all demographics and regions, coupled with a growing comfort level with online interactions for relationship building, significantly bolsters adoption rates. The market is segmented by application, with "Gay Man" applications holding the largest share, followed by "Lesbian" and "Double Sexuality" segments, reflecting the diverse user base. The increasing demand for enhanced privacy features and community spaces within these applications are also key trends shaping the market. Looking ahead, the market is expected to continue its upward trajectory, attracting substantial investment and innovation. Emerging trends include the integration of AI for personalized matches, the rise of niche dating platforms catering to specific sub-segments within the LGBTQ+ community, and the enhanced focus on safety and verified profiles to foster trust among users. While the market enjoys strong growth drivers, certain restraints such as data privacy concerns and the potential for platform saturation in highly competitive regions need to be addressed by key players. However, the overarching narrative is one of substantial opportunity, with North America and Europe currently leading in market penetration, while the Asia Pacific region presents significant untapped potential for growth. Companies like Grindr, Hornet, HER, and Tinder, among others, are at the forefront, continually innovating to capture this expanding market share and cater to the evolving needs of the LGBTQ+ dating community. The market is expected to reach approximately $9,500 million by 2033, highlighting its considerable long-term growth prospects. Here's a unique report description for a Gay Dating App market analysis, incorporating your specified elements and constraints:

This in-depth report provides a comprehensive analysis of the global Gay Dating App market, offering critical insights into its evolution and future trajectory. Spanning a study period from 2019 to 2033, with a base and estimated year of 2025, this report leverages historical data (2019-2024) and forecasts the market's growth through 2033. We delve into the intricate interplay of technological advancements, regulatory landscapes, user preferences, and competitive strategies that are shaping this dynamic industry. The market is projected to witness significant expansion, driven by increasing digital adoption and a growing demand for inclusive dating platforms. We estimate the market to reach $250 million by 2025, with an anticipated growth to $700 million by 2033, reflecting a robust Compound Annual Growth Rate (CAGR) of approximately 11%.

The rise of online dating apps has transformed how Gen Z in India explores relationships, social interactions, and casual dating. This analysis investigates dating app usage patterns, preferences, and challenges faced by individuals aged 18-25 across major Indian cities.

: ✅ Most popular dating apps ✅ Frequency & reasons for usage ✅ User satisfaction levels ✅ Challenges like safety concerns & time-wasting ✅ Preferences for features & communication methods

The study employs data visualization, statistical insights, and correlation analysis to understand the evolving landscape of online dating in India. 🚀\

User_ID: Unique identifier for each participant.

Age: Age of the user (18-25 range).

Gender: Gender identity (Male, Female, Non-binary, etc.).

Location: City of residence (e.g., Delhi, Mumbai).

Education: Education level (Undergraduate, Graduate, Postgraduate).

Occupation: Occupation type (e.g., Student, Freelancer, Intern).

Primary_App: The main dating app used by the user (e.g., Tinder, Bumble, Hinge).

Secondary_Apps: Other dating apps used, if any.

Usage_Frequency: How often they use dating apps (Daily, Weekly, Monthly).

Daily_Usage_Time: Time spent daily on dating apps (e.g., 1 hour, 2 hours).

Reason_for_Using: Purpose for using the apps (e.g., Casual Dating, Finding a Partner).

Satisfaction: Satisfaction level with the primary app (e.g., 1 to 5 scale).

Challenges: Challenges faced during usage (e.g., Safety Concerns, Lack of Matches).

Desired_Features: Features users want in dating apps (e.g., Video Calls, Compatibility Insights).

Preferred_Communication: Communication preferences (e.g., Text, Voice Notes, Video Calls).

Partner_Priorities: Attributes prioritized in a partner (e.g., Personality > Interests > Appearance).

Lovoo v3 Dating App User Profiles and Statistics

Revealing popular user traits and behavior

By Jeffrey Mvutu Mabilama [source]

About this dataset

When Dating apps like Tinder began to become more popular, users wanted to create the best profiles possible in order to maximize their chances of being noticed and gain more potential encounters. Unlike traditional dating platforms, these new ones required mutual attraction before allowing two people to chat, making it all the more important for users to create a great profile that would give them an advantage over others.

It was amidst this scene that we Humans began paying attention at how charismatic and inspiring people presented themselves online. The most charismatic individuals tended to be the ones with the most followers or friends on social networks. This made us question what makes a great user profile and how one could make a lasting first impression in order ensure finding true love or even just some new friendships? How do we recognize a truly charismatic person from their presentation on social media? Is there any way of quantifying charisma?

In 2015 I set out with researching all this using Lovoo's newest dating app version -V3 (the iOS version), gathering user profile data such as age demographics, interest types (friendship, chatting or dating), language preferences etc., as well as usually unavailable metrics like number of profile visits, kisses received etc. I was also able to collect pictures of those user profiles in order discern any correlations between appeal and reputation that may have existed at that time amongst Lovoo's population base.

My goal is forthis dataset will help you answer those questions related not just romantic success but also popularity/charisma censes/demographic studies and even detect influential figures both within & outside Lovoo's platform . A starter analysis is available accompanying this dataset which can be used as a reference point when working with the data here. Using this dataset you can your own investigations into:

  * What type of person has attracted more visitors or potential matches than others?   
  * Which criteria can be used when determining someone’s charm/likability among others    ?
  * How does one optimize his/her dating app profile visibility so he/she won’t remain unseen among other users? 

Grab this amazing opportunity now! Kick-start your journey towards understanding the inner workings behind success in online relationships today!

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How to use the dataset

To get started with this dataset first you need to download it from Kaggle. Once downloaded you should take a look at the column names in order to get an idea of what information is available. This data includes fields such as gender, age name (and nickname), number of pictures uploaded/profile visits/kisses /fans/gifts received and flirt interests (chatting or making friends). It also contains language specifics like detected languages for each user as well as country & city of residence.

The most interesting section for your research is likely the number of details that have been filled in for each user – such as whether they are interested in chatting or making friends. Usually these information points allow us to infer more about a person’s character – from jokester to serious individualist (or anything else!). The same holds true for their language preferences which might reveal aspects regarding their cultures orientation or habits.

You may also want collected data which was left out here - imagery associated with users' profiles - so please contact JfreexDatasets_bot on Telegram if you would like access to this imagery that has not yet been uploaded here on Kaggle but is intregral part of understanding what makes a great user profile attractive on these platforms according Aesthetics Theory applied in an uthentic way when considering how each image adds sentimental appeal value by its perspective content focus - be it visually descriptive; emotive narrative; personality coupled with expression mood association.. etcetera... Or simple just download relevant images yourself using automated scripts ready made via webiste Grammak where Github Repo exists: https://github.com/grammak580542008/Lovoo-v3-Profiles-Data # 1 year ago...

Finally moving ahead — keep in mind that there are other ways data can be gathered possible besides just downloading it from Kaggle – such us Messenger Bots or Customer Relationship Management systems which help companies serve...