Mereu (2016 ) Adaptation of Shannon-Weaver Communication Model for Social MediaFootball

The communication model of a Facebook live-video broadcast based on the Shannon-Weaver model: A practical example for football clubs

Shannon (1948, p. 7) Schematic diagram of a general communication system

Figure 1: Shannon (1948, p. 7) Schematic diagram of a general communication system

Note (19 Feb 2024): A similar article is available on this blog, which applies the Shannon-Weaver model to the TikTok efforts of a spectator sports brand.

Technological advancements originating from the Information Age, such as computer systems, telecommunication systems, and consumer electronics, converged into a multimedia system that made digital, computer-based and mobile communication ubiquitous (cf. Jenkins, 2006; Herczeg, 2007). This led to users adapting their behaviour in regard to how they actively and passively communicate and how they consume information and media in general (cf. Goggin, 2013; Kunz, 2014). In the following post, we will briefly discuss the state of the process of communication in regard to mobile and social media based on the Shannon-Weaver model, as depicted in Figure 1 by Shannon (1948) and Figure 2 by Burcher (2012), and apply it to communication efforts in the context of a football club.

Background

In their classic papers, Shannon (1948) and Weaver (1949) discussed a general communication system based on mathematics, which, according to Shapiro (2012), encompasses eight components:

  1. sender/source
  2. encoding
  3. message
  4. channel
  5. noise
  6. decoding
  7. receiver
  8. feedback

The feedback component was not explicitly mentioned by Shannon (1948) or Weaver (1949), but later distinctly introduced by Schramm (1954). Although the Shannon-Weaver model of communication has laid the base for communication theory in the late 1940s, Shapiro (2012) claims that the model is obsolete in times of social media, given that it targets an isolation of the message as a technical entity and does not consider textuality in the message.

Osgood (1954) had recognised the same flaw and added the dimension of interpretation. This led to the possibility of distinguishing the communication signal that carries the data and the dimension of interpreting the subjective meaning carried by the information contained in the data. Similarly, Ariel and Avidar (2015) explain that the Shannon-Weaver model attributes no intrinsic meaning to the distributed information and its process of communication is neutral, without involving psychological factors. Accordingly, in order to become information, data needs to be contextualized.

Burcher (2012, p. 18) The Shannon-Weaver model revisited

Figure 2: Burcher (2012, p. 18) The Shannon-Weaver model revisited

The above-mentioned objections on the Shannon-Weaver model become plausible when discussed in a contemporary two-way communications and social media context. Furthermore, the components need to consider more dimensions than before because of convergent media and the social attribute of social media technologies. A typical situation can portray users engaging remotely in two-way communications, sending messages that are encoded in various forms (video, audio, photo and/or text) through a plethora of digital channels. These messages can then be decoded, while being affected by physical, semantic, syntactical or other noises, extracting meaning from all the different kinds of media that users have at their fingertips. This happens before the receiver becomes the sender and either replies to the previous sender or shares it through the same or a different digital channel, as portrayed in Figure 2 and discussed by Burcher (2012, p. 17).

Before moving on to a specific example, let’s choose an appropriate definition for social media in this context. Ouirdi et al. (2014, p. 119) define social media as

“a set of mobile and web-based platforms built on Web 2.0 technologies, and allowing users at the micro-, meso- and macro-levels to share and geo-tag user-generated content (images, text, audio, video and games), to collaborate, and to build networks and communities, with the possibility of reaching and involving large audiences.”

The communication process: A Facebook live-video broadcast example

Mereu (2016 ) Adaptation of Shannon-Weaver Communication Model for Social Media

Figure 3: Adaptation of Shannon-Weaver Communication Model for Social Media (own visualization)

In this section we will depict the communication situation of a football club broadcasting a live-video through the Facebook Live function and elaborate on how the eight components of the Shannon-Weaver communication model, as discussed by Shapiro (2012) and Adler and Elmhorst (2005), drive the communication process. We will use the fictitious football club FC Xample to describe their fictitious UEFA Europa League press conference situation.

Message. In the context of a live-video broadcast on Facebook, the communication process starts with the message, this being: FC Xample wants to broadcast the press conference before its UEFA Europa League fixture through Facebook Live. Although the message might not intend to produce a two-way communication with the information it carries, it can receive responses in various forms and formats (video, photo, audio and/or text) by its viewers/receivers. Adler and Elmhorst (2005, p. 8) explain that “A message is any signal that triggers the response of a receiver.” It needs to be considered that various messages can be transmitted during the live-video broadcast, given that various topics can be discussed at the press conference. Furthermore, sports fans might want to express their positive and/or negative emotions through social media even if not specifically requested by the club (cf. Sanderson, 2011; Sutera, 2013).

Sender/Transmitter (Source). Our sender, or source of the information provided in the broadcast, is the transmitter, the person (or robot/software) that shares the information, or as Shannon (1948) describes it, “[the] transmitter […] operates on the message in some way to produce a signal suitable for transmission over the channel.” (p. 7, emphasis in original) – in our fictitious case it would be the manager, a player, or a representative staff member of FC Xample. However, an additional technician needs to be considered, who operates the live-video broadcasting device – a mobile smart phone or similar broadcasting device for example. That technical operator is an integral part of the sender or source component, given that she or he (or it, if a robot) picks up the message to finalise it in the forthcoming encoding process.

Encoding. One part of the encoding process is undertaken by the person verbalising and contextualising the information in the live-video stream. As mentioned above, this can be the manager, a player or a staff member of the club. For this first part, the quality of the encoded message is based upon several dimensions that encompass, but are not limited to, (a) verbal and nonverbal cues encoding the intentional message (Adler and Elmhorst, 2005, p. 8), and (b) the clearly defined syntax of data generating a [subjective] meaning for the broadcasted information (cf. Osgood, 1954). The second part of the encoding process is undertaken by the technical operator, who produces the message through technological tools. The quality of this part of the encoding process is based upon, but not limited to, (a) the media production of the live-video broadcast, which includes filming, lighting, audio production, screenplay, etc. and (b) transporting the readily produced media content to a digital channel – Facebook Live in this case – that will distribute the message to the viewers/receivers online.

FC Xample can prevent suboptimal encoding by testing the press conference setting in a closed environment, including briefing the transmitters – the people talking in the live-stream and sharing information – on how to behave during the filming and how to speak, as well as what information to share. Furthermore, it will be beneficial to test the technical component of the encoding process in the same test setting.

New York City FC press conference on Facebook, Sept. 10, 2016

Figure 4: New York City FC press conference on Facebook, Sept. 10, 2016

Channel. According to Adler and Elmhorst (2005), “The channel (sometimes called the medium) is the method used to deliver the message. (p. 8, emphasis in original)” The channel in our example is Facebook Live, a specific application within the Facebook social network that gives registered users the possibility to watch, comment, and share the live-video stream of the fictitious press conference broadcasted by our fictitious football club, FC Xample.

Shapiro (2012) claims that the concept of a channel is antiquated in the contemporary age of social media; it should be considered that a message is sent to a topic instead. By defining the term social media channel as “A specific medium to reach an audience through social media platforms, websites or mobile apps (adapted from businessdictionary.com)” the previous statement can be considered invalid when discussing a technological dimension of media and information distribution. Social media consists of a plethora of channels. Hence, the descriptor channel can still be deemed appropriate. Nevertheless, the argument of a meta-level in the channel component that involves the topic dimension, as argued by Shapiro (2012), is valid in the general context of social media, but not when a technological component needs to be considered as in the case at hand.

Noise. Weaver (1949) focuses on external/physical noise and explains, “In the process of transmitting the signal, it is unfortunately characteristic that certain things not intended by the information source are added to the signal. These unwanted additions may be distortions of sound (in telephony, for example), or static (in radio), or distortions in the shape or shading of a picture (television), or errors in transmission (telegraphy or facsimile). All these changes in the signal may be called noise.” (p. 12) However, in the age of social media new additions need to be considered in regard to channel noise (cf. Shapiro, 2012; Ouirdi et al., 2014). Adler and Elmhorst (2005, p. 9-10) note that there are three types of noises in the communication process: (1) external noise (physical noise) include distractions from outside of the sender or receiver; (2) physiological noise include distractions that happen within the sender or receiver based on their physiological attributes, such as hearing or visual impairment; (3) psychological noise refers to forces that affect the understanding of the receiver, such as egotism, defensiveness, hostility, fear, etc.

External noises that can affect the process of transmitting the physical/technical signal of the live-video stream on Facebook Live can include, but are not limited to, (a) an insufficiently stable or poor mobile broadband connection on the side of the sender and/or receiver, (b) too many (mobile) clients in the same WiFi network as the sender and/or receiver causing a poor connection, (c) technological issues on the Facebook website or mobile app, (d) poor audiovisuals due to low-quality video production on the side of the sender, (e) other technology-based interferences on the side of the sender and/or receiver.

Moreover, noises that can affect the live-video stream on Facebook Live in a semantic or syntactical context can include, but are not limited to, (a) poor rhetoric of the transmitter – in our case the person(s) talking and sharing information in the live-video stream or asking questions, (b) potential cultural misunderstandings in regard to chosen words, gestures and/or syntax (cf. Osgood, 1954) – i.e., our transmitter is a coach originally from South America, speaking in English (not mother-tongue) and the main audience is from Eastern Europe (not mother-tongue either), (c) suboptimal production of the camera operator – poor audiovisual production/video framing in a syntactical context, (d) viewers writing questions in the comment section that do not make sense in the context of the live-stream.

Decoding. It is essential for a sender to consider how any of the above-mentioned noise categories can affect the message and ensure a proper encoding. However, as discussed by Adler and Elmhorst (2005, p. 8), because of physical, physiological and psychological noises, there is no guarantee that a message reaches its intended receiver exactly in the way the sender intended it to be received. Senders can help with the decoding process on the receiver’s end by publishing additional content, such as text comments in the comments section of the live-stream or follow-up posts on Facebook explaining the meaning of the message. Such additional content seeks to revisit the decoding process and steer it in the intended direction.

Receiver. Adler and Elmhorst (2005, p. 8) define a receiver as “any person who notices and attaches some meaning to a message.” Burcher (2012, p. 17) applies a more contemporary view, as depicted in Figure 2, and explains that “when a professional sender puts a ‘message’ into the world it can be amplified and re-broadcast by the receiver and the re-broadcast again by subsequent receivers, and so on, with everyone adding their own thoughts, comments or reinterpretations at each stage.”

Given the social attribute of Facebook Live and social media in general, senders need to consider the magnitude of the opportunity of re-broadcasting and the potential for all re-broadcaster to attach their own thoughts, comments or reinterpretations at each stage. Hence, a thorough encoding process and an elaborated support process to facilitate the decoding of the original message with additional content might become a crucial component in the communication process to lower noises and help preventing misunderstandings. This could be achieved by applying crossmedia strategy programs as discussed by Schulz (2007, p. 24), which include multiple use, recycling, complementarity, substantive proximity, and autonomy of additional content for receivers.

Feedback. As mentioned above by Burcher (2012), receivers and subsequent receivers can reply and/or re-broadcast messages through any digital channel. This can happen intrinsically and without being requested by the sender. Furthermore, feedback to the message can be given in an open space for anyone to see. In the case at hand, Facebook Live, the comment section is visible to anyone following the lifestream. Moreover, Facebook can publish interactions between individual viewers and the FC Xample lifestream on the newsfeed of non-viewing users connected to viewing users promoting them to also join the live-stream and the conversation, hence, amplifying direct and indirect feedback to the sender. Feedback on social media can also happen outside the confines of the sender – here FC Xample. Viewers watching on Facebook Live might talk about the press conference on another digital channel, i.e. Twitter. Positive or negative feedback can be given there without the knowledge of the sender. In order for FC Xample to make sure that their message is delivered as intended, the club should monitor further digital channels and join the conversation with comments that help decoding the intended message as discussed above in the decoding and receiver sections.

In closing

The takeaway from this exercise is that the Shannon-Weaver communication model is based on the technological communication environment that was in place in the 1940s and focuses on the physical and technical component of the communication process. However, contemporary technological components, such as mobile and social media need to be added to the model, as well as semantic and syntactical components that give meaning to the data delivered through the plethora of digital channels at the fingertips of producers and users. A crucial addition to the model is, as shown in Figure 2 by Burcher (2012), that receivers become senders and can re-broadcast messages while attaching their own thoughts, comments or reinterpretations at each stage. That addition is amplified like never before through web 2.0 technology, which potentially multiplies each stage exponentially.

Bibliography

  • Adler, R. B. and Elmhorst, J. M. (2005). Communicating at work: Principles and practices for business and the professions, 8th ed. New York: McGraw-Hill.
  • Ariel, Y. and Avidar, R. (2015). Information, Interactivity, and Social Media. Atlantic Journal of Communication, 23(1), pp.19–30. DOI: 10.1080/15456870.2015.972404.
  • Burcher, N. (2012). Paid, Owned, Earned: Maximising Marketing Returns in a Socially Connected World. London: Kogan Page. [link]
  • Businessdictionary.com. (2016). Define media channel. [online] Available at: http://www.businessdictionary.com/definition/media-channel.html [Accessed 10 Sep. 2016].
  • Goggin, G. (2013). Sport and the Rise of Mobile Media. In: B. Hutchins and D. Rowe, ed., Digital Media Sport: Technology, Power and Culture in the Network Society, 1st ed. New York: Routledge, pp. 19-36.
  • Herczeg, M. (2007). Einführung in die Medieninformatik. München: Oldenbourg.
  • Jenkins, H. (2006). Convergence culture. New York: New York University Press.
  • Kunz, R. (2014). Sportinteresse und Mobile TV: Eine empirische Analyse der Einflussfaktoren des Nutzungsverhaltnes. Wiesbaden: Springer Gabler
  • Osgood, C. E. (1954). Psycholinguists: A survey of theory and research problems. Journal of Abnormal and Social Psychology, 49(4), 1–203.
  • Ouirdi, M., El Ouirdi, A., Segers, J. and Henderickx, E. (2014). Social Media Conceptualization and Taxonomy: A Lasswellian Framework. Journal of Creative Communications, 9(2), pp.107-126.
  • Sanderson, J. (2011). It’s a Whole New Ballgame: How Social Media Is Changing Sports. New York, NY: Hampton Press.
  • Schramm, W. (1954). How communication works. In W. Schramm (Ed.), The process and effects of mass communication (pp. 3–10). Urbana, IL: University of Illinois Press.
  • Schultz, S. (2007). Brücken über den Medienbruch: Crossmediale Strategien zeitgenössischer Printmedien. LIT Verlag.
  • Shannon, C. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(4), pp.623-656.
  • Shapiro, A. (2012). How Can We Redefine Information in the Age of Social Media?. BOBCATSSS Conference Proceedings (print publication, University of Amsterdam), May 2012.
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9 replies »

  1. You cite ‘Shapiro (2012)’ six times but do not include anything from Shapiro or 2012 in the Bibliography. Which Shapiro and which paper are you citing?

    • Hi Patrick. Many thanks for the hint. My bad. Just added the paper to the bibliography – it’s Shapiro (2012) “How Can We Redefine Information in the Age of Social Media?” BOBCATSSS Conference Proceedings (print publication, University of Amsterdam), May 2012.

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