February – the month of love! This phrase revokes a spectrum of emotions in different people. Some get excited, some roll their eyes and to others it’s a trigger to a traumatic experience. Whichever category you may fall into, love is undeniably viewed as an enigmatic, deeply emotional experience—one that defies logic and rationality. However, as data science advances, researchers and psychologists are uncovering patterns, behaviours and predictive models that challenge traditional notions of romance. Love and marriage is increasingly becoming unstable. Statistics from 2024 concluded with increased number of divorces, single-parenting and children born outside of marriage and a decline in the number of marriages in general¹. With about 46% of marriages ending in divorce, isn’t it time for an upgrade in our pursuit of love? So, here’s an insane idea – a scientific perspective of how we could find long-term success in love!

The Science Behind Love

Love is a complex interplay of biological, psychological and social factors. Neuroscience has shown that love activates the brain’s reward system, particularly the release of dopamine, oxytocin, and serotonin². Psychological studies indicate that factors such as attachment styles and the principles of social exchange theory⁴ play significant roles in relationship dynamics.

With big data, scientists analyse love through quantifiable means, identifying trends that were once imperceptible. Data allows us to measure compatibility, emotional responses and even predict relationship success with increasing accuracy! Sounds like a new storyline to a rom-com?

The Role of Data in Modern Dating

Online dating platforms such as Tinder, OkCupid, and eHarmony use algorithms to match users based on their interests, behaviours, and preferences. These platforms rely on the following for efficiency and personalised results:

1. User Data and Preferences through personality questionnaires: dating apps can match individuals with similar values and interests. (eHarmony uses a compatibility matching system based on psychological traits and relationship behaviours) ⁵
2. Machine Learning Algorithms refine match suggestions based on likes, messages, and time spent viewing profiles ⁶
3. Predictive Analytics: Studies have shown that certain patterns, such as response times and frequency of communication, can predict relationship success or failure ⁷

Compatibility Metrics

Traditional matchmaking was often based on intuition or shared cultural values, but today’s approach is much more precise. Research has identified several key factors that contribute to compatibility:

• Personality Traits: The  Myers-Briggs 16 personalities suggest that people with similar levels of openness, conscientiousness and emotional stability tend to have more successful relationships.⁸
• Communication Styles: Relationship scientists have found that couples who engage in active listening and constructive conflict resolution have higher satisfaction rates. A common test done during blind dating/relationship counselling is the love language quiz to better understand your partner’s communication preference aligning with Chapman’s Five Love Languages theory ⁹.
• Shared Interests and Values: A study from 2012 showed that couples with aligned long-term goals and values have higher success rates in their relationships ¹⁰.
• Physical and Emotional Chemistry: While physical attraction is important, studies suggest that shared experiences and emotional support play a larger role in long-term satisfaction ¹¹

Predicting Relationship Longevity with Data

Who needs tarot reading and fortune tellers when one of the most compelling applications of a data-driven approach to love is its ability to predict relationship longevity! Researchers like John Gottman have developed mathematical models that can predict divorce rates with over 90% accuracy based on communication patterns ¹². Key predictors of relationship success include:

• The 5:1 Ratio: Successful couples have five positive interactions for every negative one ¹⁰
• Conflict Resolution Styles: Avoiding contempt and defensiveness significantly improves relationship stability.
• Emotional Responsiveness: Partners who consistently respond to each other’s emotional needs are more likely to stay together ¹².

The Ethical Implications of Data-Driven Love

Now to answer the tough questions: Can love truly be quantified? Are algorithms limiting human spontaneity? You may argue that reducing love to data points may oversimplify its complexity and lead to a lack of emotional depth in relationships. True, the beauty of love is the emotions exchanged and the butterflies it gives you. Predicting longevity and analysing your compatibility score can ruin something that could have been a match made in heaven. Afterall, we live in a spontaneous environment where anything is possible. Hence, you can turn to algorithm as an option of your pursuit of love and not make it your sole bible!

References

1. Stevenson, B. and Wolfers, J. (2007). Marriage and Divorce: Changes and their Driving Forces. The Journal of Economic Perspectives, [online] 21(2), pp.27–52. doi:https://doi.org/10.1257/jep.21.2.27.
2. Fisher, H. E., Aron, A., & Brown, L. L. (2005). Romantic love: An fMRI study of a neural mechanism for mate choice. Journal of Comparative Neurology, 493(1), 58-62.
3. Hazan, C., & Shaver, P. (1987). Romantic love conceptualized as an attachment process. Journal of Personality and Social Psychology, 52(3), 511-524.
4. Thibaut, J. W., & Kelley, H. H. (1959). The Social Psychology of Groups. Wiley.
5. Carter, S., & Buckwalter, J. (2009). eHarmony’s matching algorithm and relationship success. Journal of Relationship Research, 12(3), 205-220.
6. Rudder, C. (2014). Dataclysm: Love, Sex, Race, and Identity—What Our Online Lives Tell Us About Our Offline Selves. Crown Publishing.
7. Joel, S., Eastwick, P. W., & Finkel, E. J. (2017). Is romantic desire predictable? Machine learning applied to initial romantic attraction. Psychological Science, 28(10), 1478-1489.
8. Zárate-Torres R, Correa JC. How good is the Myers-Briggs Type Indicator for predicting leadership-related behaviors? Front Psychol. 2023 Mar 2;14:940961. doi: 10.3389/fpsyg.2023.940961. PMID: 36936015; PMCID: PMC10017728.
9. Flicker SM, Sancier-Barbosa F. Testing the predictions of Chapman’s five love languages theory: Does speaking a partner’s primary love language predict relationship quality? J Marital Fam Ther. 2025 Jan;51(1):e12747. doi: 10.1111/jmft.12747. Epub 2024 Oct 17. PMID: 39420529.
10. Finkel, E. J., Eastwick, P. W., Karney, B. R., Reis, H. T., & Sprecher, S. (2012). Online dating: A critical analysis from the perspective of psychological science. Psychological Science in the Public Interest, 13(1), 3-66.
11. Gottman, J. M., & Silver, N. (1999). The Seven Principles for Making Marriage Work. Harmony Books.
12. Hazan C, Shaver P. Romantic love conceptualized as an attachment process. J Pers Soc Psychol. 1987 Mar;52(3):511-24. doi: 10.1037//0022-3514.52.3.511. PMID: 3572722.
13. Gottman, J. M., & Levenson, R. W. (2002). A two-factor model for predicting when a couple will divorce. Journal of Family Psychology, 14(1), 42-58.