Barbara Silva

Let’s start with you. Who are you, and what lens do you bring to understanding people online?

I work at the intersection of data, social behavior, communication, and public policy. My background in Sociology and Public Policy helps me understand people online not merely as users or consumers, but as social actors embedded in cultural, institutional, and historical contexts.

I see digital environments as extensions of the public sphere, where narratives, symbolic disputes, emotions, and power dynamics unfold. For that reason, my approach combines quantitative analysis of large-scale data with a qualitative, interpretive reading of conversations, paying close attention to language, framing, visibility dynamics, and silences.

When analyzing people online, I aim to go beyond what is being said to understand why it is being said, by whom, in which contexts, and with what potential effects. This lens allows me to turn fragmented conversations into strategic insights without flattening the complexity of the public debate.

For me, understanding people online is an exercise in qualified listening and analytical responsibility. The goal is not simply to produce insights, but to faithfully translate digital voices in ways that support informed decision-making by brands, organizations, and governments—while respecting the diversity of perspectives and meanings that emerge from these interactions.

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What’s a working theory you have right now about how people behave online?

I believe that online behavior is strongly shaped by incentives of visibility and belonging. In digital environments, opinions, emotions, and narratives are often expressed not only as reflections of individual beliefs, but as social performances oriented toward recognition, engagement, and alignment with specific groups.

This means that platforms do more than host conversations—they actively structure behavior. Algorithms, content formats, and engagement metrics influence what is said, how it is said, and how intensely it circulates. Emotions such as outrage, fear, or enthusiasm tend to travel faster and farther because they are more rewarded by platform dynamics, contributing to the amplification of polarized or simplified positions.

At the same time, these environments do not eliminate human complexity; they reorganize it. Individuals move between multiple roles, communities, and modes of expression, adapting how they communicate to different audiences, topics, and contexts. For this reason, interpreting online behavior requires caution: volume should not be mistaken for consensus, engagement for relevance, or visibility for legitimacy.

My working theory is that understanding digital behavior demands looking beyond explicit content and examining the sociotechnical contexts that shape online action, as well as the symbolic and relational motivations that sustain participation in digital spaces.

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What’s an insight you surfaced that you still think about? What one stuck with you?

I have been thinking a lot about how, in many online debates, silence can be just as meaningful as volume. Across different analyses, it became clear that the absence of certain voices or perspectives does not necessarily signal disengagement. More often, it reflects fear of exposure, fatigue with public debate, or the perception that some digital spaces are not safe or welcoming.

This insight stuck with me because it challenges a common assumption in social analysis: that relevance is measured primarily through visible engagement. In many cases, highly amplified narratives create the illusion of consensus, when they actually represent only the most mobilized or most comfortable groups speaking publicly. Meanwhile, more moderate, technical, or ambivalent positions remain underrepresented.

Since then, I’ve paid closer attention to who is not speaking, which topics fail to gain traction, and when conversations begin to thin out. These absences reveal important dynamics around power, the social costs of participation, and the boundaries of what feels sayable in certain contexts.

For me, this insight reinforces the importance of interpreting social data with care and responsibility, recognizing that what appears on platforms is only a partial reflection of the broader social conversation.

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What’s the weirdest rabbit hole your work has ever sent you down? And what did it teach you?

I have spent an absurd amount of time tracking conspiratorial narratives and political mobilization strategies during electoral processes in Brazil and other Latin American countries. What began as monitoring election-related conversations gradually revealed complex ecosystems connecting institutional politics, disinformation, local cultural references, humor, and transnational conspiracy frameworks.

As I followed these conversations over time, it became clear how certain narratives travel across borders, are adapted to specific national contexts, and gain traction through fear, outrage, and distrust of institutions. In many cases, engagement was driven not only by electoral preferences, but by a sense of belonging to groups that see themselves as holders of an “alternative truth” or privileged knowledge.

This experience taught me that election monitoring goes far beyond measuring volume or voter sentiment. It requires understanding language, symbols, informal leadership, and distributed coordination dynamics that operate across digital platforms. It also reinforced the importance of approaching these phenomena with analytical rigor and responsibility, recognizing that even the weirdest paths reveal consistent patterns in how people construct meaning and identity, and engage in political action in digital environments.

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What skills or mindsets do you think the next generation of analysts will need?

Analysts need to combine strong technical skills with a more advanced critical and interpretive mindset. Mastery of tools, data, and analytical models areessential, but they were never and will never be enough. Moving forward in an increasingly complex information environment, the key differentiator will be the ability to contextualize, interpret, and question data rather than simply process it.

One of the most important mindsets will be active and responsible listening. Analysts must recognize that social data represents real people embedded in cultural, political, and emotional contexts. This requires ethical sensitivity, awareness of bias, and attention to the impacts of insights on decision-making—especially when those insights are amplified or mediated by artificial intelligence systems.

Developing systems thinking will also be critical. Understanding how platforms, algorithms, AI models, and visibility incentives shape online behavior enables analyses that are more robust and less reactive to noise. Equally important is the ability to engage critically with automated systems—knowing when to trust them, when to challenge them, and when to complement them with human judgment.

Finally, the next generation of analysts will need strong translation skills: the ability to turn complexity into clarity without losing nuance. In an AI-driven environment, communicating limitations, uncertainty, and multiple interpretations will be just as important as presenting results, ensuring that insights remain useful, responsible, and well-contextualized.

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What’s a niche community, account, or corner of the internet you’re watching right now? And why?

At the moment, I’ve been paying close attention to communities, accounts, and initiatives operating in less visible corners of the internet that explore the use of social listening and social intelligence to understand urban dynamics and inform public policy. These spaces range from specialized forums and independent newsletters to applied academic projects, civic innovation labs, and collectives analyzing digital conversations about public transportation, urban infrastructure, access to services, and overall quality of life in cities. One example comes from journalist Raul Lores, who engages the public across different social media platforms through the project “SP nas alturas,” talking about São Paulo and other Brazilian cities from elevated perspectives, exploring urban infrastructure, architecture, mobility, and how the built environment shapes everyday life.

This area interests me because these niches function as social interpretation laboratories. It is within these environments that everyday perceptions about mobility, infrastructure, safety, public services, and territorial inequalities emerge more spontaneously and in greater detail—often before they appear in official indicators or in broader public debates.

These communities show how social data can serve as a complementary layer of urban diagnosis, capturing lived experiences and daily frustrations that rarely surface with the same speed or granularity in traditional administrative data. They point to the potential of social listening to help support urban interventions that are more sensitive to local contexts and to people’s concrete living conditions.

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Last non-work thing you read that shaped your thinking?

Recently, I discovered some independent fashion designers in Brazil and was so hooked by their creations that I ended up reading a bunch of texts, interviews, and materials about them. Rather than focusing on fashion as a set of trends, these readings highlighted fashion as a cultural expression, a site of collective identity, and a vehicle for belonging.

What stood out to me was how some Brazilian designers and brands build narratives deeply connected to territory, memory, race, gender, and everyday life. This process closely mirrors what I observe through social listening, where culture and identity are constructed in distributed, relational, and highly symbolic ways.

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