Frontiers in Physics (Jun 2022)
Quantifying Award Network and Career Development in the Movie Industry
Abstract
In show business, awards are conferred to persons and films to provide incentives to performers’ future career development through periodic film festivals and events. In this work, we focused on exploring the growth and dynamics of the film award system, the structure of the award network, and the relationships between historical performance, collaborations, and future career success of performers in the movie industry. We collected data from IMDb, which covers more than 3.5K movie events for 520K individuals with their award-winning and career records for over 90 years. By using network analysis and regression models, we find several novel results. At first, we found the exponential proliferation of awards across all genres of films and all professions of individuals and the uneven distribution of the number of awards in careers across time. More than 30% of the performers have won multiple awards. Second, we built an award network to reveal the interlocks between awards based on multiple award-winning phenomena. We found that for prestigious awards, 47% of the linkages were over-representative than the expectations from the null model. Furthermore, the performers’ collaboration network was highly clustered, exhibiting a high propensity of linkages between awarded performers. Lastly, our regression models revealed that multiple factors were related to performers’ early career success and award winning. Specifically, we showed that along with the performers’ historical achievements, their collaborators serve an important role in award winning after being nominated, with the scope and depth of the impact differing in the awards’ prestige. This work has strong implications for the harmonious dynamics of the movie industry and the career development of performers.
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