Computer mediated Communication
Influence of Computer-Mediated Communication on Expectancies
Paralinguistics is “the science of vocal cues that accompany our speech” (Amant, 2007). Paralinguistic / paralanguage cues consist of the pitch, volume, tone, modulation, speech rate, and intonation. When socializing with new people on a face-to-face basis, we often prejudge even before we speak to them. These preconceptions are often based on a variety of non-verbal cues like gestures and appearance. If we were to first interact with same individuals via phone, we would have less non-verbal cues to draw on, but we could still use verbal cues like the rate of speech, pauses, in speech and accents to prejudge them.
If the same scenario were acted out via computer-mediated communication, such as social networking sites, your impressions would be based on text message interactions alone. According to DeLamater & Myers (2007), the accuracy of communication is greatly enhanced by the use of multiple cues, as opposed to a single communication channel (180). Human beings often base their impressions about other people early on during interactions. Paralinguistic cues complement our speech to communicate our messages in clearer ways (Holland, 2008).
. Listeners, on the other hand, use these cues to gauge our intentions and form expectations about us. Computer Mediated Communication interactions do not have any paralinguistic cues. There is thus the need for insight on how this affects the expectations or preconceptions that people form of each other in Computer Mediated Communication interactions.
Past Research and key theories
Past research into this question has resulted in a variety of conclusions. The Social Context Cues Theory proposes that the absence of paralinguistic cues in Computer Mediated Communication makes it highly ambiguous (Epley & Kruger, 2005). As a result, we depend on our personal stereotypes to make preconceptions about the other person’s character. Computer Mediated Communication thus allows the persistence of expectancies or stereotypes due to the absence of paralinguistic cues ordinarily relied on to question them(Holland, 2008). A highly standardized experiment found that preconceived impressions could not be challenged by Computer Mediated Communication interactions as compared to phone interactions (Epley& Kruger, 2005).
Conversely, the social information processing theory suggests that potential deficiencies of Computer Mediated Communication are indemnified by the use of text based non-verbal cues like ‘Laughing Out Loud’ (LOL) and “mhhh”. The usage of emoticons in Computer Mediated Communication provides an emotional setting to users (Walther & D`Addario, 2001). Computer Mediated Communication users can thus express socio-emotional content with only written text via these non-verbal cues and timing of the messages. A recent social experiment showed that live Computer Mediated Communication chats could challenge pre-interaction stereotypes better than phone communication (Walther et al, 2010).
However, these experiments were hampered by a variety of limitations. One limitation was the use of faulty experimental designs, which did not correctly simulate natural Computer Mediated Communication interactions. Other experiments lacked control parameters hence making it difficult to establish causal relationships. The current experiment has improved on this by balancing realism and control.
Experiment Goal and Hypotheses
The aim of this experiment is to find out if paralinguistic cues in the Computer Mediated Communication interactions were sufficient to challenge the expectation that the target individual was introverted.
The hypotheses for this experiment are:
1. According to the social cues theory it is predicted that the presence or absence of paralinguistic cues in Computer Mediated Communication interactions will not have an effect on personality trait ratings.
2. According to the Social Information Processing Theory, it is predicted that the presence or absence of paralinguistic cues in Computer Mediated Communication interactions will have an effect in personality trait ratings.
The sample used had participants divided into three groups A, B, and C. Group A was the paralinguistic cues group. It had one hundred and twenty males and three hundred and forty two females with the average age of 20.7years. The standard deviation for this group was 5.3. Group B was the plain text group with one hundred and twenty five males and three hundred and eight females with an average age of 21.2 years. Standard deviation for this group was 5.4. Group C, the Control group, had one hundred and thirty one males and three hundred and twenty nine females with an average age of 20.9 years. Standard deviation for group C was 5.1. The total sample had one thousand, three hundred and fifty five participants with a total average age of 20.9 years. The standard deviation for the whole experiment was 5.23.
The researchers used internet-connected computers to conduct the experiment. They facilitated the observation and communication stages. Participants were directed to observe a past CMC activity. This made it more controlled and realistic across different scenarios. A profile stimulating the expectation in participants that a target individual was introverted was designed. Participants then looked at this profile then observed the target individual communicating with an uncontrolled third party. Participants were then divided in two. One group looked at basic text interaction while the other looked at a realistic paralinguistic communication with many cues hinting that the target was an extrovert. The text used for the interactions was made from a real paralinguistic interaction from which all cues were removed to produce a basic text interaction. Therefore, the conversations had identical contents apart from the Paralinguistics introduced.
The research design used was the independent measures design. It was ideal for this experiment as it avoided order effects like tiredness or practice (Gravetter & Forzano, 2009). There were three levels of Independent variables or experimental conditions used. These were the control group, the group with the basic text interaction and the group with the paralinguistic interaction. The dependent variable was the basic text interaction while the independent variables were the paralinguistic cues and groups of participants.
The results supported the second hypothesis demonstrating that the presence of paralinguistic cues does indeed have an effect on pre-conceived expectations. The results are thus consistent with the Social Information Processing Theory.
Amant, K. (2007). Linguistic and cultural online communication issues in the global age. Hershey, PA: Information Science Reference.
DeLamater, J. D. & Myers, D. J. (2007). Social Psychology. Belmont, CA: Thomson Higher Education
Epley, N., & Kruger, J. (2005). What you type isn’t what they read: The perseverance of stereotypes and expectancies over email. Journal of Experimental Social Psychology, 41, 414-422.
Garrison, A., Remley, D., Thomas, P., & Wierszewski, E. (2011). Conventional faces: Emoticons in instant messaging discourse. Computers and compositions, 28, 112-125.
Gravetter, F. J. & Forzano, L. B. (2009). Research Methods for the behavioral sciences. Belmont, CA: Wadsworth Cengage learning
Hancock, J. T., & Dunham, P. J. (2001). Impression formation in computer-mediated communication revisited: An analysis of the breadth and intensity of impressions. Communication Research, 28, 325-347.
Holland, S. (2008). Remote relationships in a small world. New York: Peter Lang.
Messaris, P. & Humpreys, L. (2006). Digital Media: transformations in human communication. New York: Peter Lang
Walther, J. B. & D’Addario, K. P. (2001). The impacts of emoticons on message interpretation in computer-mediated communication. Social Science Computer Review, 19, 324-347.
Walther, J. B., Deandrea, D. C., & Tong, S. T. (2010). Computer-mediated communication versus vocal communication and the attenuation of pre-interaction impressions. Media Psychology, 13, 364-386.
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