Why do people hold such mixed opinions about migration, blending compassion and concern? This question reflects a common dilemma among Colombians, as evidenced by sentiments like this:“I believe Venezuelan migrants deserve help, and many are good people just looking for a chance. But I also worry about the strain on jobs and services for locals.”
Opinions are rarely clear-cut. In a debate, some people strongly defend their views; others disagree entirely, and many fall somewhere in between—agreeing with certain points while remaining uncertain about others. Every opinion is shaped by a mix of emotions, beliefs, and experiences. How can we better understand this complexity to see where people truly stand?
During a study I conducted in Colombia on attitudes toward migrants as part of the “Computational Framework for Assessing Absorptive Capacity” project, I discovered that opinions are not always straightforward. Many people expressed mixed feelings—supporting migrants in some respects while voicing concerns in others. To capture these nuanced positions, I used Latent Class Analysis (LCA), a statistical technique that classifies people into groups based on underlying patterns of their responses to certain items.
Using LCA was like uncovering hidden communities within a crowd, each defined by distinct attitudes and concerns. This technique allowed us to move beyond surface-level opinions and recognize the deeper patterns shaping people’s views. It revealed the richness and complexity of human attitudes, offering insight into how individuals navigate emotionally charged topics.
Through this approach, our study identified three distinct groups:
Supporters with Economic Concerns – Those who trust and support migrants but worry about economic impacts.
Indifferent or Neutral Individuals – Those who hold no strong opinions either way.
Opponents with Positive Connections – Those who generally oppose migration but have had positive personal interactions with migrants.
These categories illustrate just how layered and multifaceted our thoughts and feelings can be.
Psychology helps explain why such mixed opinions exist. Human attitudes are rarely fixed or extreme. Theories by Ajzen (2005) and Verplanken & Orbell (2022) suggest that attitudes are shaped by an interplay of thoughts, emotions, and experiences. These theories reinforce the value of tools like LCA, which allow us to capture this variety by grouping people into classes that reflect their diverse and shifting stances.
In conclusion, LCA serves as a powerful tool for uncovering the nuanced and dynamic nature of human attitudes. By identifying hidden patterns, it helps us better understand the needs and concerns of diverse groups. This deeper understanding is essential for developing solutions that resonate with people’s real experiences and fostering meaningful social change. By identifying these latent classes, we can design more targeted public policies that address the concerns of each group.
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