Information in Ancient Human Societies

EE376A (Winter 2019)

By Paula G.

How did information present itself in ancient human societies? Is the availability of information and communication means correlated with empire growth, measured by population?

The goal of this project was to produce descriptive statistics on the history of human communication and information using data from the Seshat Databank. A crucial part was to clean and format the available data.

The Seshat dataset is a collection of data related to the social and political organization of human societies. It roughly focuses on the time period between the Neolithic and Industrial Revolution (ca. 4,000 BCE to 1,900 CE). Currently, 30 locations, called natural geographic areas (NGAs), around the world are included. Data is recorded for polities which occupied these 30 NGAs in the previously specified time-frame. The unit of analysis is a polity, where a polity is defined as an independent political unit. Polities can range in scale from villages to states and empires. For more information, please see Turchin et al. (2017) and Turchin et al. (2015).

The following map gives an overview of the location of the NGAs.

Location of the NGAs

The information / communication related variables in the Seshat Databank include features related to information storage (e.g. presence of written records or presence of scientific literature), features related to precise recording of information (e.g. presence of lists, tables and other classifications)  and features related to information transmission (e.g. presence of courier and post services).

The following plot shows correlations of selected information features with population on a polity-year level. The size of the points as well as the coloring is proportional to the strength of the correlation. All correlations below are positive and significant.

Correlation of Information Features with Population

Postal services are highly correlated with population, even more than the presence of written records. Of course, none of these correlations imply causality.

Individual features such as the ones shown above can be combined into a measure of “information capacity”. Here, “information capacity” is defined as the fraction of information related features which were present. For example, if there were ten information features and a polity possessed three of these, then the polity’s information capacity would be 3 / 10 = 0.3.

Another important source of variation in the data is time, measured yearly. Years BCE are indicated by a negative sign and years CE are indicated by a positive sign. The following animated plot shows how “information capacity” varies by time and by polity population. The points are colored by NGA.

Correlations: Year – Population – Information Capacity (colored by NGA)

The animated plot suggests that there is some positive correlation between “information capacity“ and population. As there are many information features included in the data, hierarchical clustering was conducted. Clustering was implemented on information features only. Similar to above, the following animated plot shows how “information capacity“ varies by time and polity population for five different clusters.

Correlations: Year – Population – Information Capacity (colored by Cluster)

Clustering was able to detect different groups, mostly with regard to the measure of “information capacity”. However, it seems that polities with higher “information capacity”, regardless of time, tend to have larger populations.

Overall, there is some suggestive evidence that “information capacity” is positively correlated with growth, as measured by population. The analysis of causality is left for future research.

Outreach Event:

The main results from this descriptive and exploratory analysis were used to design a game: The Information Game.  The Information Game is inspired by “Settlers of Catan” by Klaus Teuber (1995). I developed two versions of the game: A simpler version which was played at the outreach event as well as a more complex version, which was distributed as a present. More information on these games is available here.

The goal of the game is to accumulate as many information points as possible. Information points are earned by increasing the “information capacity” of one’s growing empire. For example, “information capacity” can be generated by constructing post offices or by acquiring the possibility of writing. Contrasting the original game, the extension brings in additional balance as even small empires can win, as long as their “information capacity” is high enough!

Outreach Event

Literature and Disclaimer:

This research employed data from the Seshat Databank under Creative Commons Attribution Non-Commercial (CC By-NC SA) licensing. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official positions, either expressed or implied, of the Seshat Databank, its collaborative scholarly community, or the Evolution Institute.

Turchin P. et al. 2017. Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization. PNAS.

Turchin P. et al. 2015. Seshat: The Global History Databank. Cliodynamics 6(1):77–107.

Klaus Teuber. 1995. The Settlers of Catan. Catan Studio.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.