Reply All, a podcast by Gimlet Media about the internet, has a recurring segment called “Yes Yes No.” In this segment, Gimlet CEO Alex Blumberg sits down with the two hosts, Alex Goldman and PJ Vogt, and asks them to explain something he’s found on social media, usually twitter. In each case, Alex reads the tweet, his voice sounding extremely perplexed, and then the co-hosts attempt, if they can, to decode all the levels of meaning behind what at first glance reads like nonsense. This segment highlights the difference between the signal-code-transmission model and meaning system models.
When Alex fails to understand a tweet, it isn’t because of a breakdown in the signal transmission model.
Figure 1: Knight 2012, Hartzell 2017, Tomwsulcer 2014
Above, I’ve created a very simplified signal transition model for “tweeting,” using Shannon’s design (Gleik 2011). Briefly, the user/information source, composes a message. This message is encoded (mediated through the smartphone’s touchscreen interface). The digitized message, now bytes, is transmitted in data packets over a wireless network, through the internet, where it is received by Twitter. Twitter then decodes these data packets and it’s software interprets the information, classifying, indexing, and storing it as well as running many other protocols for updating it’s platform. When twitter’s users launch the software application on their smartphones, the software sends an encoded request for information (again through wireless networks and the internet). After decoding this request, Twitter then encodes a new message in bytes made up of the combined information and transmits it back to the smartphones of users. Twitter’s application software receives the encoded information, decodes it, and displays it digitally on the screen. The platform is designed in such a way that the original message is reproduced as inscribed by the original user, but is combined with information provided by other users of the platform. The “noise” in the diagram above constitutes anything that interrupts the transmission of the data packets.
Unlike a text message designed for an individuated destination, Twitter is designed for a community of users. Twitter is designed to pattern match, which allows for the classification of information, creating a taxonomy of meaning. This classified information is aggregated and displayed on its platform. Additional algorithms create new information by tracking user interaction to determine the way information is displayed. This gives users, like Alex Blumberg, the option to see what information is getting the most attention. When Alex reads a confusing tweet, his inability to understand what is says isn’t due to a system breakdown, it is because the information Twitter is relaying comes from various users all with different reference points for interpreting what they are seeing on their digital displays. Alex has the ability to read the text and digital images below, but he doesn’t know what they mean.
Figure 2: Yes Yes No 2017
If the tweet above also has you confused, you can listen to the episode here.
Denning and Bell describe information as always being comprised of two parts “sign and referent.” Humans determining meaning by “the association between the two” (Denning and Bell, 2012, 477). The signs, or the symbols we perceive, are nothing unless we are able to associate them to a subject or idea. In the case above, the tweet and image work together to convey a whole series of meanings that can only be understood once the context is explained. In the “Yes Yes No” segment, Alex Goldman and PJ spend time providing the necessary history for decoding meaning, and once they do, the tweet can be read with ease.
Humans are constantly creating new links between symbols and things they perceive. These new linkages are expressed through language, which is socially constructed and constantly in flux. The orderly system of signal transition outlined by Shannon, which is essential for successfully mediating symbols through digital and electronic transmission, can never apply to the meaning of the messages without first freezing the relationship between meaning and language. And, as relationships are subjective, frozen language would then be forever encoded with other social constructs, such as power dynamics, and would reflect only this historical moment. Day describes this as “fulfilling the two paramount concerns for the U.S. during the Cold War period: controlling and idealizing linguistic and social normativity, and, relegating linguistic and social marginality and political contestation to minority or curiosity status, or simply, to being social or linguistic “noise.” (Day 2000, 811).
Day is extremely critical of using statistical methodologies to ascribe meaning to symbols; however, Denning and Bell’s article see ascribing meaning, the process of linking the sign and the reverent, as new information. That new information can then be processed by machines. This is a constantly generating system, as opposed to the lockdown described by Day. Twitter is designed to use algorithms to pattern match user preferences and promote content the software has statistically determined is relevant to its user’s interests. It is also designed to target advertisements toward specific demographics that the software has statistically determined are likely to buy certain products. In this sense, it is processing “meaning.” It should then be determined, to what extent these algorithms are fulfilling Day’s concerns and freezing social norms, or to what extent the systems is constantly adapting to knew information?
“#106 Is That You, KD? – By Gimlet Media.” Gimlet Media. Accessed October 18, 2017. https://gimletmedia.com/episode/106-is-that-you-kd/.
Day, Ronald E. “The ‘Conduit Metaphor’ and the Nature and Politics of Information Studies.” Journal of the American Society for Information Science 51, no. 9 (2000): 805-811.
Denning, Peter J., and Tim Bell. 2012. The information paradox. American Scientist 100 (6): 470-477.
Gleick, James. The Information: A History, a Theory, a Flood. (New York, NY: Pantheon, 2011).
Hartzell, Kathryn. Smartphone Screenshots. 2017
Knight, Gary. Now, Instead of Texting Each Other, You Can Text Other People. March 11, 2012. Friends with Mobile Phones Uploaded by JohnnyMrNinja. https://commons.wikimedia.org/wiki/File:Friends_with_Mobile_Phones.jpg.
Tomwsulcer. English: Young People Using Their Smartphones at a Party. The Ever-Present Use of Smartphones for Multiple Purposes Has Led Some Writers to Describe Young People as the “Thumb Tribe” or “Thumb Generation”. July 7, 2014. Own work. https://commons.wikimedia.org/wiki/File:Young_people_texting_on_smartphones_using_thumbs.JPG.
“Yes Yes No.” Yes Yes No. Accessed October 18, 2017. http://yesyesnos.tumblr.com/.