#teamgina #RHOMelbourne #bigdata #followme
Big Data is considered a ‘currency across industry’ (Woodford, 2014) and in today’s new media-focused world, is what is created when we tweet, post a Facebook status or even look up something online. A particular feature of this week’s lecture on Big Data that interested me was Twitter and its involvement in the creation of data.
In terms of new media, Twitter is a breeding ground for the creation of data through hashtags, trending topics and multiple networks. Hashtags not only serve a purpose for sharing thoughts about which Melbourne Housewife is your favourite (#teamgina for your information), but also provide a simple way to collect data for analysis (Woodford, 2014). Beyond hashtags however, are networks that represent data through interpersonal communication about similar topics (Bruns and Moe, 2013). These networks allow groups of users who share similar interests to communicate in ‘personal publics’ (Bruns and Moe, 2013) and participate in follower-followee networks. This ‘meso’ level of the networks is only superseded by the ‘micro’ level, which is concerned with replies on Twitter (Bruns and Moe, 2013). This particular type of interaction is considered mind-bogglingly extraordinary to a fifteen-year-old girl who spends her life spamming Harry Styles with hundreds of tweets, only to have him respond and make her dreams come true. This type of personal interaction is fleeting on Twitter, but is hardly a possibility on other social networking sites such as Facebook.
Speaking from experience (six out of eight of the Real Housewives of Melbourne have answered me AND Gina and Chyka follow me, big news I know), it does make you feel personally connected to that other person, whether or not it’s only for a few seconds. That something about what you said made them respond to you, not the hundreds of other people attempting to get a response at the same time. This type of interpersonal communication serves a further purpose rather than simply tweeting under a hashtag, or following your idol on Twitter in the hope that one day, they would follow back (language warning for the video).
Until recently, the notion of tweeting under a hashtag has been unique to Twitter (until Facebook decided to job on the bandwagon). Still, it’s not often you see your Facebook news feed littered with comments from every friend about the same show. Unless it’s the weather report, in which case all of my Facebook friends are apparently meteorologists. This idea of discussing and sharing opinions about a particular television show or Hollywood awards event under a particular hashtag allows us to understand how we interact with each other, both nationally and internationally. Twitter has allowed us to communicate without barriers, share opinions with the world and connect with the people we admire most, all while creating big data to be nit-picked and analysed by bigger powers.
Should we be worried? Possibly, but unless we’re having a Too-Much-Information Tuesday or Follow-Me-Around-Friday moment on Twitter, what’s the problem with picking which Housewife’s side you’re on? It may provide an approximation of which housewife has a larger following, and could even encourage a retweet if you mention them, but that’s about it. Rock on, #teamgina.
Reference List
Bruns, A & Hallvard, M. 2013. “2. Structural Layers of Communication on Twitter.” In Twitter and Society: An Introduction. Accessed May 8, 2014. http://mappingonlinepublics.net/2013/11/04/announcing-twitter-and-society/
Woodford, Darryl. 2014. “New Media, Big Data and Telemetrics (guest lecture by Darryl Woodford)”. Accessed May 8, 2014. http://www.dpwoodford.net/wp-content/uploads/2014/02/KCB206-Big-Data-Lecture_Small.pdf









