Disillusion forecast: can big data prediction help us to face the imperfect reality?FMP
Field of Study
In the age of big data, wearable devices, medical records and browsing history are stored and analysed in every moment, data scientists attempt to predict our health conditions, personal preference, shopping behaviour and even emotion.
The deluge of data not only for more business opportunities, this information helps us explore human experience and behaviour out of unconscious(C. Rudder, 2014). If we have more understanding of human nature, will the human emotions be more predictable? With big data, it might be the best opportunity to think of affective forecasting (Wilson, T., & Gilbert, D. 2003), will predictions of future emotions assist us with better determination? Once the result of predictions do not satisfy our anticipations, how do we face the gap between hope and loss, deal with the response uncontrollable emotion?
According to the prediction of various likelihood based on big data, more the possible options would be provided, helping us adjust a better schedule and become more efficient, even fix the upcoming failure. Consider the application of emotion prediction, why can’t we predict the likelihood of having a successful relationship or break up using big data?
The devised mathematical model (J.Gottman, 2002) was claimed that it can predict with 94% accuracy which couples will divorce. The two applied mathematicians analysed hundreds of videotaped conversations between couples in Professor Gottman’s relationship research institute. They also analysed pulse rates and other physiological data to provide a “bitterness rating” for each conversation. For the disastrous marriage, what mattered was not the dispute itself, but a couple’s communication pattern during the argument. A lot of fighting that couples engage in is a failure to make emotional connections.
Nowadays, big data can be used to store and analyse our communication record with our partner via instant messaging applications. The most common words or phrases between a couple in conversations might reveal the positive or negative meaning behind. According to the research on effects of texting in romantic relationships(S. Luo, 2014), texting among couples predicts personalities based on the attachment theory, compared with other communication channels (e.g., face-to-face, phone, and etc.), avoidant people are usually uncomfortable to express emotion directly and tend to select the less intimate communication channel—texting to maintain their close relationship, while people who use texting along with other communication methods in large volume might show their anxiety to keep the relationship. The lack of satisfaction and the dysfunctional communication patterns might reflect the insecure relationship. Big data can be used here to estimate the influence in close relationships through texting usage and communication pattern, predicting whether a relationship will succeed or not.
But even Big data can indicate our relationship decline, make alert and even recommendations, are we able to address the imperfect relationship frankly? “Nothing is more sad than the death of an illusion.” The novelist Arthur Koestler states. Love consists of both illusion and reality. Even if we can predict what gonna happen probably in the relationship with the help of technology, it is still unconfident to accept how imperfect we are and face the disillusion of love.
Disillusion might not be a pleasant experience. Humans by nature are motivated by the anticipation, but when we discover that the truth is not as fantastic as we believed, it would be lost and disappointed.
In the movie Eternal Sunshine of the Spotless Mind (M. Gondry, 2004), it depicts the story that when the relationship turns sour, a couple select to undergoes a procedure to have each other erased from their memories. Rewinding the lost memories show the audience the love they ever had, and how did it fade out. In the end, a couple without original memories meet again and still fall in love, when they understand that they did have broken up before, the present happiness and hope might be gone accompanied with the possible repeat occurrence, should they chose to begin again? We won’t know whether the decision is correct or not, but it is significant to face the imperfect relationship and self with honest.
- Look at the contextual research of affective forecasting and what type of data reveal emotion unconsciously.
- Ethnographical research of people in different stages of relationships, talking about expectations. Do they have any experience to disguise themselves to reach the expectation from their partner, or on the contrary, over-idealise their partner on the other hand?
- Quantitative research on the usage of messenger apps. Can the message amount and interaction custom tell us more about communication pattern?
- Collect the information related to relationship prediction and list it in the visualise way.
- Make some tangible model to express the opposite emotion such as happiness and pain, hope and fear, anticipation and disillusion, make the audience interact with these models then get the feedbacks.
- What should the format of “guide” and “forecast” be? Look at how other guide and forecast design displaying their information and convey the conception.
We all know that it would be hard to face the real self and unideal reality. I aimed to design the product as the guide for facing disillusion, it would be the reminder of the potential problems in the relationship, especially the overidealize expectation. The point does not just follow the inductions then everything would be fine, the idea of disillusion forecast is making people learn to deal with disillusion, and find a new perspective to view their perception to the relationship and themselves.
Execution Duration: 3 months(2017 July to Sep)
- Contextual research on communication pattern, data and emotional prediction. [2 weeks]
- Primary research on discussing the expectation in the relationship, and what the role of messenger apps play inside. [3 weeks]
- Visualise and analyse the collected information. Look at the reference of guides and forecasts. [3 weeks]
- Produce the tangible emotion model and test the reaction from the audience. [4 weeks]
Wilson, T., & Gilbert, D. (2003). Affective Forecasting. Advances In Experimental Social Psychology
C. Rudder, (2014) Dataclysm: Who We Are (When We Think No One’s Looking)
J.Gottman , (2002) A Two-Factor Model for Predicting When a Couple Will Divorce
S.Luo, (2014). Effects of texting on satisfaction in romantic relationships: The role of attachment. Computers in Human Behavior
M. Gondry, (2004) Eternal Sunshine of the Spotless Mind