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How I Created a Social Recommendation Network in Brazilby@1uc4sm4theus

How I Created a Social Recommendation Network in Brazil

by 1uc4sm4theusNovember 21st, 2024
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Hello everyone,


This is the first time I’m writing about RecomendeMe here on HackerNoon. The site has been evolving in small steps, mainly because of my limited time (working full-time). In my current job, I’m increasingly distanced from coding and closer to decision-making; at most, I do a code review every now and then. My passion has always been programming, so RecomendeMe helps me stay connected to what I love most: coding ideas or cool things that can help people!


How to Start a Social Network – Solving the Cold Start Problem

I get it. We’ve all seen the movie. You know, the one where Jesse Eisenberg plays Mark Zuckerberg, hacking his way through university servers to launch what would become Facebook. It’s an iconic moment, and let’s be honest, it sparked a lot of dreams about creating “the next big thing.” For some, it was a challenge; for others, a source of inspiration. But here’s the thing: it’s not that simple.


Hollywood loves a good Eureka moment, full of dramatized breakthroughs and rapid success. In reality, building a platform—especially a social network—is more about patience, persistence, and solving problems you might not even see coming. And the biggest of those problems? Getting users.


The Social Network - David Fincher


Without users, a platform is like an abandoned amusement park: all the potential for joy and engagement, but eerily empty. In the world of content-driven social networks, this challenge is often called the Cold Start Problem. It’s a techy term, but at its core, it’s straightforward: a recommendation system—or any similar platform—can’t make good suggestions or connections without data. And data comes from users.

The Cold Start Problem: Breaking It Down

Imagine launching a new social network. Your platform might have all the bells and whistles—polished design, an intuitive interface, maybe even some killer features—but if no one is using it, you’re stuck. There are no interactions to analyze, no preferences to study, and no way to personalize the experience. That’s the Cold Start Problem in action. It’s like trying to start a conversation in a room full of strangers who’ve never met.


Cold Start


This challenge is especially tricky for new communities. Even if you have a great catalog of content, it’s hard to offer meaningful recommendations without user interaction. Without data about what people like, your system can’t understand their needs, let alone fulfill them.

How RecomendeMe Faced the Challenge

When I started RecomendeMe, my biggest hurdle was personalization. How do you tailor recommendations when your platform is brand-new and users haven’t shared much yet? Luckily, I had a lifeline: a group of culture-loving friends. These early adopters brought their enthusiasm and content, helping me bypass the initial emptiness that plagues many platforms. They promoted the idea, shared recommendations, and created a foundation of activity that made the site feel alive.



From there, things grew organically. For instance, while RecomendeMe includes a field for users to add descriptions, only a handful actually used it. This small detail revealed something important: the way people interact with the platform shapes how useful and engaging it feels. Every click, share, and omission taught me more about what users needed—and how to adapt.

Lessons Learned

The Cold Start Problem isn’t just a technical challenge; it’s deeply human. People won’t stick around if they don’t feel seen, understood, or valued. Early success comes not from algorithms alone but from community—the shared passion of like-minded individuals. RecomendeMe became more than a project for me; it became a way to connect with others, to learn, and to build something meaningful together.


As I continue developing the platform, I’m reminded daily that what makes a network thrive isn’t just the technology behind it, but the people who bring it to life.



How to Develop a Social Network – Personalization and Differentiation

When I started RecomendeMe, my primary goal wasn’t just to build a functional platform. It was to deeply understand the process of creating a social network, step by step. I wanted to see how every choice, big or small, would shape the way people interact with the site.


Currently, the platform operates without a login system, which means recommendations are made by users anonymously or with freely chosen usernames. While this simplicity has its charm, it also creates a problem: there’s no personal connection to the recommendations. Without profiles or bios, it’s hard to create the feeling that a real person is behind each suggestion, which diminishes authenticity and trust. This is something we aim to address by introducing features like user accounts, where individuals can log in, personalize their profiles, and create a sense of identity on the platform.

The Power of Individual Profiles

Profiles are more than just a username or avatar—they’re a gateway to human connection. Allowing users to share personal information, interests, and preferences opens up opportunities for meaningful interactions. It’s not just about making recommendations more personal; it’s about fostering a sense of community. When people can see who is behind a recommendation, they’re more likely to trust it, relate to it, and engage with it.


RecomendeMe Music


Moreover, individual profiles provide a foundation for personalized content. By understanding a user’s preferences, we can tailor recommendations to their tastes, making the experience more enjoyable and relevant. This also sets the stage for deeper engagement, as users feel the platform “understands” them.

Finding Our Unique Place

For RecomendeMe to thrive, it needs to stand out in a crowded digital landscape. Platforms like Instagram, Letterboxd, and Goodreads have already carved out their niches, excelling in visual storytelling or niche-specific recommendations. RecomendeMe’s focus is different: we want to create a space that celebrates cultural diversity while prioritizing the human aspect of recommendations. It’s not just about algorithms or trends—it’s about people, their passions, and the connections they form through shared experiences.


RecomendeMe Movies


Solving the Fragmentation Problem

One of the challenges I’ve observed in today’s digital ecosystem is the fragmentation of interests. People create accounts on specialized platforms like Letterboxd for movies, Goodreads for books, and Spotify for music. While these platforms excel in their respective domains, there’s no unified place where all this information comes together. This fragmentation makes it harder for users to explore their interests holistically.



RecomendeMe aims to bridge this gap. Imagine a platform where you can discover not only the movies your friends love but also the books they’re reading and the music they’re listening to—all in one place. This integrated approach simplifies how people interact with the content they love and creates opportunities to explore new things outside their usual preferences or social circles.

The Vision for RecomendeMe

At its core, RecomendeMe isn’t just a platform; it’s an idea. It’s about bringing people together through the things they love, making it easier to discover, share, and connect. Personalization isn’t just a feature—it’s the foundation of creating meaningful experiences. And differentiation isn’t about being flashy or trendy; it’s about staying true to a vision that values authenticity, community, and discovery.

In a world where algorithms dominate, RecomendeMe strives to bring the human touch back to recommendations. After all, the best suggestions don’t come from data—they come from people who genuinely care.


How to Develop a Social Network – Finishing and Delivering the Product


The beauty of a social product is that it’s never truly finished. There’s always room for improvement, new features to add, and ways to stand out. RecomendeMe has gone through multiple iterations to reach its current stage as a cultural recommendation network. It’s been a journey of refining the platform, learning from mistakes, and listening to the people who use it.


One of the most valuable lessons I’ve learned is the importance of feedback. Whether it’s from close friends, passionate users, or even casual visitors, every piece of input shapes the platform. Early adopters, especially those from TabNews, played a critical role in pointing out what worked and what didn’t. They gave suggestions, shared their experiences, and showed me how the platform could better serve their needs. This collaboration has been at the heart of RecomendeMe’s growth.


What motivates me to keep going is the understanding that RecomendeMe isn’t just a project—it’s a living, breathing community. Each update and feature isn’t about making the code more elegant (though that’s satisfying in its own way); it’s about creating something meaningful for the people who use it.

The Human Factor in Tech

RecomendeMe could have been written in any programming language—Python, Ruby, Go, you name it. Sure, some languages might offer better performance or flexibility, but that’s not the point. What truly sets the platform apart isn’t the tech stack; it’s the people. The users who share recommendations, the friends who offer encouragement, and the communities that engage with it—all of them bring the platform to life.


A social network thrives on connections, not just between users but between the creator and the audience. Every decision I make—whether it’s designing a new feature or tweaking an existing one—is informed by this relationship. It’s not about perfection but about progress, about continuously finding ways to make the platform more valuable and inclusive.

Always Evolving

What excites me most about RecomendeMe is that it’s never static. There’s always something to enhance, a new challenge to tackle, or a fresh idea to explore. Each iteration brings the platform closer to its ultimate goal: to become a space where people can share, discover, and connect over cultural content. It’s this sense of possibility that keeps me pushing forward.


In the end, what makes RecomendeMe special isn’t just the recommendations or the algorithms behind them—it’s the community that supports and builds it. That’s where the magic happens. And as long as there are people willing to engage, share, and dream, there will always be more to create.


A Manifesto for Breaking the Bubble

In today’s digital age, one of the biggest challenges we face is escaping our own echo chambers. Algorithms, while powerful, often serve to reinforce the same patterns—showing us content we already like, pushing us deeper into familiar bubbles. As a result, it’s harder than ever to stumble upon something truly new and unexpected. The thrill of discovery has been replaced by the monotony of repetition, where every feed feels like a mirror reflecting back what we’ve already consumed.


But it wasn’t always this way.


There was a time when recommendations felt more personal, more human. Think back to the golden age of video rental stores, where a handwritten note on a VHS box might say, “A must-watch for sci-fi fans!” or the casual conversation with the clerk who knew your taste better than any algorithm ever could. Remember flipping through rows of records, chatting with fellow music lovers about their favorite hidden gems, or exchanging tips with friends about that one amazing game tucked away in the corner of the store?


These moments were simple but profound. They were rooted in human connection, curiosity, and the joy of sharing. You weren’t being guided by data-driven predictions; you were guided by people, by passion, by stories.


Games


Disc Store


RecomendeMe was born from a desire to bring that feeling back—to create a space where recommendations feel alive, authentic, and personal again. It’s about rediscovering the joy of finding something new, not because an algorithm thought you might like it, but because someone genuinely wanted to share it with you.


We don’t need to settle for curated sameness. We can break free from the bubbles and bring back the spirit of exploration. With each recommendation on RecomendeMe, we aim to recapture that magic of wandering into uncharted territory, whether it’s a book you’ve never heard of, a film that takes your breath away, or a song that speaks to your soul.


Let’s build a community where discovery thrives, where human connection drives recommendations, and where the unexpected is celebrated. Together, we can step outside the algorithm and into a world of endless possibility—just like we used to do, back when finding something new was as easy as walking into a store and having a conversation. RecomendeMe might not become the biggest social network on the planet, or even the best recommendation platform out there. I can clearly see that Letterboxd, for instance, is already moving in the right direction, fostering a strong community around cultural recommendations. But at some point, we have to acknowledge the irreplaceable value of the human touch. Algorithms are powerful—they’re fast, efficient, and capable of processing unimaginable amounts of data. But they lack authenticity. They don’t experience joy when discovering a hidden gem, and they don’t smile when sharing a beloved piece of content with a friend. That’s what makes human recommendations unique: they come from a place of passion and connection, not from cold calculations. RecomendeMe is my attempt to bridge that gap. To remind us that, while technology can help us organize and scale, it’s the human factor that gives meaning to the experience. It’s the conversations, the shared excitement, and the moments of serendipity that truly make recommendations special. So, let’s create something different—a space where algorithms assist but don’t define, where people can share what they love, not just what trends dictate. Because at the end of the day, the best recommendations come not from the smartest system but from the most genuine hearts.


Because the best discoveries are always the ones we didn’t know we were looking for.