Nature of Online Interactions Behaviors and Relationships - Literature review Example

Table of Contents Synthesis: On the Nature of Online Interactions, Behaviors and Relationships 3 Rough Outline 7 Detailed Outline 9 References 13 Synthesis: On the Nature of Online Interactions, Behaviors and Relationships The general topic is the use of large data sets from the Internet to analyze human behavior, social relationships, and human events. This paper synthesizes the work of Jon Kleinberg on large data sets and insights into society and human behavior on the one hand, and a study indicating reduced levels of social anxiety as measured in different factors affecting social anxiety. Synthesizing the two articles, this paper asserts that online social interactions reflect both old and emerging paradigms of social relationships dynamics, that need to be studied using new methods in order to glean appropriate insights into them (Yen et al, 2012; Kleinberg n.d.). The research question we pursued is this: In what ways are online social interactions different, and how can we exploit the large amounts of generated date on our social interactions to glean insights into old and emerging human relationships and behavioral dynamics? How are online social relationships and interactions different, and how do we exploit the power of the Internet to analyze them? (Yen et al, 2012; Kleinberg n.d.). Kleinberg shows us that large data sets analysis can upend the way we have done things in the past, and offer new and better ways to do things. Kleinberg touches on the predictive power of large data sets made available from popular aggregation sites on the Internet, for instance. Such include the photo-sharing site Flickr, email and major social media platforms. To do this he uses several examples, for instance, such as the use of Flickr tags to map out the world and its major geographical aggregation points, and the use of email for instance coupled with powerful data mining tools to be able to track the progress and decline of human relationships as they applied to Kleinberg's personal case. This kind of approach produces something new in terms of how we can manipulate data to provide us with insights into why we do the things we do. The power comes from the way social media, such as Flickr, have aggregated user-generated digital trails of their activities and interactions with places and other people. Moving forward, this offers a vast resource for scientists, marketers, businesses, and sociologists, among others, to be used to glean insights into behavior and into the nature of human relationships. One take is that of social relationships and social interactions essentially being the same in the real world as they are online, with social media and related data giving us new ways to examine and analyze the nature of those interactions and relationships in ways that were not possible before. Likewise, the take is that because of the unprecedented power of online data in this regard, new ways of looking at and analyzing the data have to be devised in order to properly exploit this new reality. This new reality presents a new set of opportunities for new insights into human relationships, behavior, and interactions (Yen et al., 2012; Kleinberg, n.d.). The work of Yen et al. (2012) on the other hand further reinforces the thesis that online interactions are different, and that online social relationships yield new sets of dynamics with regard to how human beings relate to one another, behave, and are impacted by their social relationships. In this particular study, it has been found that there is a lesser amount of social anxiety associated with online interactions in comparison to offline or real-world interactions. In particular, subjects that showed reduced social anxiety were found among those who are suffering from depression, high levels of social anxiety, high behavioral activation system or BIS scores, and high behavioral inhibition system or BIS scores. The study notes too, that in particular, the impact of BIS on social anxiety is diminished when subjects interact online, charting a future path for research that puts focus on BIS when treatment modalities for social anxiety are coursed online. In general, the study notes that given the reduced levels of social anxiety in online interactions, the Internet in general holds out new hope for treating social anxiety (Yen et al, n.d.) It is worth noting that the two articles chosen for this paper both reinforce the thesis that online social interactions reflect both old and emerging paradigms of social relationships dynamics, that need to be studied using new methods in order to glean appropriate insights into them. In the Kleinberg article, it is clear that social media and the Internet in general, with its vast amounts of digital trails of social interactions and individual human behavior, is a treasure trove for understanding and gleaning insights into human relationships and behavioral dynamics. What this means is that whereas data was limited before, they are in profusion now, something unprecedented, and new tools and techniques for analyzing the data ought to validate old findings and insights, while yielding new ones. Where the insights confirm what is already known about human behavior and relationships, what is new is the kinds of data and analytical tools and techniques that are at the disposal of the researchers and scientists. On the other hand, what the Yen et al. (2012) article so clearly demonstrates is that online interactions represent a new social reality, that is characterized by new sets of dynamics with regard to human relationships and impact on human behavior and well-being. In this instance, what is new is that social anxiety for patients with different mental illnesses is reduced online, or is at a lower level in comparison to interactions in the real world. The implication of this is an affirmation of the thesis that online interactions represent a new reality, that needs to be examined as such, with an eye towards new social and behavioral dynamics. In the case of the second article, the implications include being able to come up with new treatments for previously intractable ailments, in this case social anxiety and related mental illnesses (Yen et al., 2012; Kleinberg, n.d.) In conclusion, this paper proves the thesis that online social interactions and behavioral dynamics are different and represent a new reality, that when considered as such, opens new horizons into analyzing and gleaning insights into those (Yen et al., 2012; Kleinberg, n.d.) Rough Outline General Topic: The general topic is the use of large data sets from the Internet to analyze human behavior, social relationships, and human events (Yen et al., 2012; Kleinberg, n.d.). Research Question: In what ways are online social interactions different, and how can we exploit the large amounts of generated date on our social interactions to glean insights into old and emerging human relationships and behavioral dynamics? How are online social relationships and interactions different, and how do we exploit the power of the Internet to analyze them? (Yen et al, 2012; Kleinberg n.d.). Focus of research question: How are social interactions, relationships, and behaviors different/the same online and offline, and what insights can be gleaned from them? (Yen et al, 2012; Kleinberg n.d.). Answers to research question: 1. Kleinberg shows us that large data sets analysis can upend the way we have done things in the past, and offer new and better ways to do things. Kleinberg touches on the predictive power of large data sets made available from popular aggregation sites on the Internet, for instance. Such include the photo-sharing site Flickr, email and major social media platforms (Kleinberg, n.d.) 2. The work of Yen et al. (2012) on the other hand further reinforces the thesis that online interactions are different, and that online social relationships yield new sets of dynamics with regard to how human beings relate to one another, behave, and are impacted by their social relationships. In this particular study, it has been found that there is a lesser amount of social anxiety associated with online interactions in comparison to offline or real-world interactions. In particular, subjects that showed reduced social anxiety were found among those who are suffering from depression, high levels of social anxiety, high behavioral activation system or BIS scores, and high behavioral inhibition system or BIS scores (Yen et al., 2012).. Detailed Outline Introduction: Background Info: The general topic is the use of large data sets from the Internet to analyze human behavior, social relationships, and human events. This paper synthesizes the work of Jon Kleinberg on large data sets and insights into society and human behavior on the one hand, and a study indicating reduced levels of social anxiety as measured in different factors affecting social anxiety. Synthesizing the two articles, this paper asserts that online social interactions reflect both old and emerging paradigms of social relationships dynamics, that need to be studied using new methods in order to glean appropriate insights into them (Yen et al, 2012; Kleinberg n.d.). Body Paragraph 1: Topic Sentence: Kleinberg shows us that large data sets analysis can upend the way we have done things in the past, and offer new and better ways to do things. Kleinberg touches on the predictive power of large data sets made available from popular aggregation sites on the Internet, for instance. Such include the photo-sharing site Flickr, email and major social media platforms (Kleinberg, n.d.). Support 1: To do this he uses several examples, for instance, such as the use of Flickr tags to map out the world and its major geographical aggregation points, and the use of email for instance coupled with powerful data mining tools to be able to track the progress and decline of human relationships as they applied to Kleinberg's personal case (Kleinberg, n.d.). Conclusion: One take is that of social relationships and social interactions essentially being the same in the real world as they are online, with social media and related data giving us new ways to examine and analyze the nature of those interactions and relationships in ways that were not possible before. Likewise, the take is that because of the unprecedented power of online data in this regard, new ways of looking at and analyzing the data have to be devised in order to properly exploit this new reality. This new reality presents a new set of opportunities for new insights into human relationships, behavior, and interactions (Yen et al., 2012; Kleinberg, n.d.).. Body Paragraph 2: Topic Sentence: The work of Yen et al. (2012) on the other hand further reinforces the thesis that online interactions are different, and that online social relationships yield new sets of dynamics with regard to how human beings relate to one another, behave, and are impacted by their social relationships (Yen et al., 2012) Support 1: n particular, subjects that showed reduced social anxiety were found among those who are suffering from depression, high levels of social anxiety, high behavioral activation system or BIS scores, and high behavioral inhibition system or BIS scores. The study notes too, that in particular, the impact of BIS on social anxiety is diminished when subjects interact online, charting a future path for research that puts focus on BIS when treatment modalities for social anxiety are coursed online. In general, the study notes that given the reduced levels of social anxiety in online interactions, the Internet in general holds out new hope for treating social anxiety (Yen et al, n.d.) Conclusion: The article supports the thesis that online interactions represent a new reality that yields new modes of human interactions, with new impacts on human behavior and human interaction dynamics (Yen et al., 2012). Body Paragraph 3: Topic Sentence: It is worth noting that the two articles chosen for this paper both reinforce the thesis that online social interactions reflect both old and emerging paradigms of social relationships dynamics, that need to be studied using new methods in order to glean appropriate insights into them. (Kleinberg, n.d.; Yen et al, 2012). Support 1: In the Kleinberg article, it is clear that social media and the Internet in general, with its vast amounts of digital trails of social interactions and individual human behavior, is a treasure trove for understanding and gleaning insights into human relationships and behavioral dynamics. What this means is that whereas data was limited before, they are in profusion now, something unprecedented, and new tools and techniques for analyzing the data ought to validate old findings and insights, while yielding new ones. Where the insights confirm what is already known about human behavior and relationships, what is new is the kinds of data and analytical tools and techniques that are at the disposal of the researchers and scientists (Yen et al., 2012; Kleinberg, n.d.) Support 2: On the other hand, what the Yen et al. (2012) article so clearly demonstrates is that online interactions represent a new social reality, that is characterized by new sets of dynamics with regard to human relationships and impact on human behavior and well-being. In this instance, what is new is that social anxiety for patients with different mental illnesses is reduced online, or is at a lower level in comparison to interactions in the real world (Yen et al., 2012; Kleinberg, n.d.) Conclusion: The two articles support the thesis in complementary ways, reinforce the assertion that online relationships and interactions yield old and new insights into them (Yen et al., 2012; Kleinberg, n.d.), Conclusion In conclusion, this paper proves the thesis that online social interactions and behavioral dynamics are different and represent a new reality, that when considered as such, opens new horizons into analyzing and gleaning insights into those (Yen et al., 2012; Kleinberg, n.d.) References Kleinberg, J. (n.d.). What Can Huge Data Sets Teach Us About Society and Ourselves? Future Science Yen, J. et al. (2012). Social Anxiety in Online and Real-Life Interaction and Their Associated Factors. Cyberpsychology, Behavior and Social Networking 15 (1) Read More