The Sociology 101 model focuses on the mood of people within a society. The population consists of
two groups, the Passives and the Agressives, and people can switch between the two. While
randomness essentially governs the variation within the model, variables also control how many
citizens are passive and how many are aggressive. Based on user-set values, these variables can
affect how many citizens wind up in each group. A graph displays the change in mood over time,
which is a tool that could be useful for political leaders who wish to survey and respond to
citizens' mood. Students using this model will be able to study and evaluate factors that decide a
population's mood as well as discuss the applications and modern methods for determining it.

Background Information

People gage the mood of a populace for a number of different reasons. Politicians can use the data
to determine how well they are supported by the citizens, businesses can decide the best product
to market, and scientists can assess the overall health of a country. In the 2012 presidential
election, twitter was used extensively as a means to judge the population's support for certain
candidates. Based on the results of tweets, politicians would change their image or strategy in an
attempt to appeal to the maximum number of voters. In this model, users can change the variables
that influence the passive or aggressive mood and find which much be changed to produce the
desired result.

Science/Math

The fundamental principle in this model is HAVE = HAD + CHANGE. At any time, the following
procedures are running to determine the mood of the population:

The number of passive people are calculated based on the pacification factor

The number of aggressive people are calculated based on the feralization factor.

The number of passive and aggressive people are plotted on a graph over time

The above changes show that the process is largely user-independent. This is true in real life, as
well. While the variables that influence mood can usually be changed, the desired results cannot
be directly affected.

Teaching Strategies

Teachers may wish to introduce this model with a series of questions and hypotheses. Ask students
the following questions regarding sociology. Answers to these questions may be referred to later
after using the model to assess the students' predictions.

What factors could influence a population's mood?

How would the mood of the population affect the productivity of the city?

Who could benefit by knowing the mood of a population? Why?

What modern methods are there for determining a population's mood?

Implementation:

How to use the Model

This model has a number of variables that may be changed in order to produce a different outcome:

Coping factor determines the ability for people to overcome and deal with difficulties

Outlook determines the positive or negative attitudes of people to the world

Stewing controls the amount that people brew over and remain agitated

Provocation controls the chance that someone will react when provoked

All of these factors work in the calculations that determine the overall mood of the people.
Coping factor and outlook determine the extent to which people will tend to be pacifists, while
stewing and provocation determine the chance people will be more feral. The variables may be
changed by clicking the Synthesim button (represented by a green triangle with sliders behind it
or a running man) and dragging the appropriate sliders. In this mode, results will be
instantaneously calculated and the results plotted on the graph. For a complete tutorial on
Vensim, visit the following resource:
http://shodor.org/tutorials/VensimIntroduction/Preliminaries.

Learning Objectives:

Understand the most influential variables in a population's mood and how mood information can be
useful

Objective 1

A population's mood can be affected by several different variables, such as the average level of
income, the form of government, etc. This model focuses on a few key variables in this system. Ask
students to find the most influential variable in the system and answer the following questions:

Which variable has the most control over the amount of people who are of a particular mood? How
do you see this in the real world? Is this accurate?

Does either of the two outcomes (Passive or Aggressive) seem to have a bias in this simulation?
Explain.

Why does the graph seem to fluctuate? What does this imply about how the model is programmed,
and what does this account for in real-world scenarios?

Imagine the graph was assessing the passiveness or aggressiveness of a town. What could the
leaders do with this information?

How would the mood of one person affect the mood of another? Is this accounted for in the model?
Explain.

Extensions:

Extension 1

Elsa Kim and Sam Gilbert wrote in their report on moods expressed in tweets, "The body of tweets
about Michael Jackson's death also offers an opportunity to explore strategies for sentiment
analysis-the process of determining the attitude of a speaker or speakers towards a particular
topic in a large corpus of text." This is one way that people are finding the moods of people in
the modern world. Ask students to brainstorm ways to determine population mood and ask them to
experiment with one of their ideas. The following questions will help guide their thought:

What are some limitations to the methods the class came up with? In what situations would each
be appropriate?

What could you learn by knowing the mood of the people? What external factors do you think
affect mood the greatest?

Extension 2

The Sociology 101 model depicted mood determined by several different factors. What if this was
reversed? Can happiness affect productivity? Have students research this topic and answer the
following questions:

What conclusions did you find regarding happiness' affect on productivity? How did the
researchers come to this conclusion?

What sampling methods did they use to collect the data?

Do you see the variables from the Sociology 101 model at work in any of the research done?
Explain.

The Sociology 101 model had many similar aspects to a SIR model in that the user is able to assess
the change in a population over time based on specific variables. In the SIR with Scroll Bars
model, the functionality is also similar to the Sociology model. The user is presented with a
graph depicting the spread of a disease over time. A few different scroll bars are available to
easily see how much one variable affects the overall outcome of the simulation. Teachers who
choose to use this model in their curriculum will find the analytical skills students learned in
the Sociology 101 model will be more than applicable to SIR with Scroll Bars.

The Rumor Mill model does not graph the change in people's moods over time, though it does analyze
the spread of a rumor through a population. In this model, the functionality is very similar to
that in the Sociology 101 model, but there are a few more variables that work into the outcome. In
the Sociology 101 model, there were a few external variables that indirectly affected the final
calculations. With the Rumor Mill model, that concept is further discussed and expanded.