Gamasutra is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Gamasutra: The Art & Business of Making Gamesspacer
Modeling Opinion Flow in Humans Using Boids Algorithm & Social Network Analysis
View All     RSS
February 29, 2020
arrowPress Releases
February 29, 2020
Games Press
View All     RSS

If you enjoy reading this site, you might also want to check out these UBM Tech sites:


Modeling Opinion Flow in Humans Using Boids Algorithm & Social Network Analysis

September 28, 2006 Article Start Previous Page 5 of 8 Next

Examples and Results

Small Population Example – Baron KingMaker
Our small population example is the network of people around the ‘King Maker’ the person who can to a large part decide who will be made king. In other games, this person could be the King, or a Prime Minister, Warlord, etc. A diagram of our network is shown in Figure 5. All connections around the Baron are positive. (He doesn’t allow people he doesn’t like into his inner circle).

Figure 5 . The people around Baron KingMaker, and how much he values their opinions.

Other than the influence on the Baron there are very few connections. Advisor 1 and Advisor 2 do not like each other, and so almost always offer opposing opinions – which is why the Baron does not pay much attention to them. The Baron’s wife’s opinion flows entirely from her hairdresser – who has a surprising amount of influence in this game world. The hairdresser’s opinion in turn could be partially derived from the average public opinion6. The player may be able during the game to discover the influence of the hairdresser, and lobby her directly.

For a network this small, it is easy to calculate the average alignment seen by the Baron. The total of all connections going to the Baron is 20, so we will sum the alignment score of each individual times the weight of their connection divided by 20.

Avg. Alignment = AlignAdvisor1 * (1 / 20) + AlignAdvisor2 * (1/20) + AlignAdvisor3 * (5/20) + AlignWife * (6/20) + AlignProtege1 * (1/20) + AlignProtege2 * (1/20) + AlignMentor * (5/20)

The average alignment around the Baron may be used to help determine his responses. For example, if the people around the Baron are pushing him in one direction, it might not take quite as much gold from the player to push him further in that direction. We have not tried this, but it may work well in open ended and non-structured games such as never ending quests.

Large Population Results – Books and Battles
John and Richard compete to convince an overwhelming majority of the public that they are the rightful heir and king. A population is set up with its opinions generally mixed. At round 50, an influential writer prints a treatise explaining why King John is the rightful king. On round 100, King Richard takes a castle (which many perceive as a Kingly thing to do.) Battles and Books don’t normally come together in the game world, but we are bringing them together in our simulated court of public opinion.

In Figure 6 is shown some example results. Each of the 5 runs shown had populations of 10,000 actors. The average number of links each actor had was around 20. The computation time to do all 150 game rounds took about 100 seconds, so during a normal game this would be a negligible amount of time. The set up of the random links did take 5 minutes for the first population and then three and half minutes thereafter. So the set up is something that we will look further into how to optimize.

Figure 6 . Five runs of populations of 10,000 people influenced by the events of King John and King Richard.


Large Population Results – Schism
Humans tend to self-segregate. Even in multi-cultural societies, members of one group may feel superior to members of another group, and do things to differentiate themselves. The existence of groups indicates that there will be more linkages on average inside a group than across the group boundary. In terms of ideas, this may mean that an idea generally accepted in one group may not necessarily be desirable in the other group.

For our large heterogeneous population example, we have a population of 10,000 people. Alphas make up 10% of the population. They have a high degree of contempt for the betas, and that is reciprocated7. In our example, something that was not open to discuss has suddenly became something that people can have an opinion. When only ‘Coke’ exists, one can only pick ‘Coke’. Once ‘Pepsi’ arrives, there can be revolution in the air, and people can have an opinion on which is better.

Figure 7 shows how the average alignments re-adjust when something that not a question is now open for discussion. In this example the Alphas have a vested interested in maintaining the old system. (See the section on Leadership following this article.) To help represent this in the game world, we are not letting 20 of the Alphas (because they benefit so greatly from the current system) change their opinions.

Figure 7 . Our populations of Alphas and Betas in general hold different opinions on the topic at hand.

In our small toy universe we have demonstrated the viral spread of ideas, and recreated the reformation.

Article Start Previous Page 5 of 8 Next

Related Jobs

Heart Machine
Heart Machine — Culver City, California, United States

Technical Designer
Purdue University
Purdue University — West Lafayette, Indiana, United States

Assistant Professor in Game Development and Design
Heart Machine
Heart Machine — Culver City, California, United States

Gameplay Engineer
Vicarious Visions / Activision
Vicarious Visions / Activision — Albany, New York, United States

Senior Software Engineer

Loading Comments

loader image