Everyone knows the risks with online dating. They know that people can lie and turn out to be the complete opposite of what they expected them to be, but still the hopes that their soul mate is online looking for them is too tempting to turn down. So what happens when you do meet that person that turns out to be that person with a couple of loose screws that everyone warns you about meeting online? Just ask Kman.
Kman saw a woman’s profile and corresponded with her on the phone and Internet for weeks until they finally set a date. Regardless of the danger signs, which now seem obvious to him, like her avoidance of her divorce, how she always sounded drunk on the phone, and her insistence on him spending the night before they even went out, he decided to give her a chance. When he showed up for his date, she, her ten-year-old son, her mom, and her husband’s brother promptly greeted him. But wait, it gets better. They then proceeded to have a photo shoot where everyone got a chance to get a picture with him. Needless to say, the rest of the night did not get any better, after he learned that, yes, she was still married, but her husband was in jail for robbing a bank, twice, for crack money. Lets just say that the date ended early while she made one last attempted by appealing to his… manhood.
Kman should’ve have stuck by the three strikes your out rule. I want to look at the warning signs Kman noticed in relation to some theories. First, the Social Presence Theory and Reduced Social Context theories together state that CMC will lead to impoverished, often negative impression formation. In this case, the limited cues Kman picked up on like how she always sounded drunk and wanted to get to know each other at a tavern turned out to be red flags after all. These were factors that she did not do a good job at hiding from him which leads me to the Hyperpersonal Theory which states that we rate people based on fewer characteristics (breadth) with more intensity. When they finally left the virtual world, these characteristics and warnings were loud and clear. Even though these theories say that we get limited cues in CMC, Kman’s nightmare definitely proved that these limited cues can be all you need to throw someone in the loony bin.
Read his story for a good laugh: http://onlinedatingnightmares.com/datingstories/index.php?PHPSESSID=ba10e45498439976f2c0956690f86c4a&topic=4.0
Subscribe to:
Post Comments (Atom)
2 comments:
Hi Jillian,
I love your blog. It's hilarious. It's funny how Kman had all these signals about the woman but he still decided to go meet her. I can't even imagine when he was greeted by practically her whole family except for the jailed husband! And then to have his photo taken with each member of the family, which must be so awkward.
With the warnings the woman was giving, Kman should have developed a negative impression of her according to the social presence theory and reduced social context cues. However, he seemed to neglect the poor qualities of her personality. It's a good thing that when he finally met her, the warnings became loud and clear.
I really enjoyed reading your post, and I think the story that you found is absolutely hysterical. You did a great job drawing on theories that we learned earlier this semester. In terms of the theories that we are currently discussing in class involving leaving virtuality, I think that your example of a mixed mode relationship relates to Berger and Calabrese’s Uncertainty Reduction Theory (URT). With URT, a positive outcome for leaving virtuality only occurs if uncertainty is reduced. In your example, URT predicts a negative outcome for leaving virtuality. Although the woman that Kman spoke with online gave some odd warning signs, she also must have shared enough positive traits to have encouraged Kman to think it would be a good idea to meet. However, upon their ridiculously absurd meeting, Kman’s uncertainty regarding the woman increased after meeting her family and learning more about her life. Such an increase in uncertainty leads to the negative outcome that URT can sometimes predict when leaving virtuality.
Post a Comment