As I began reading this week, a passage that stuck me was, in summary; Online images become ‘networked’ when users like, share, comment or tag them, and also when platforms and engines format, filter, feed and recommend them to others (Lister, M 2009). This means ANYTHING we put online is networked, because as soon as we post, a set of protocols have already begun tracking our content. A visual example of this was shown in our week three course lecture conducted by Elaine Si Leong:

Sourced From

This clarifies how Information is distributed on the internet. Information is not held on any one node and every point holds information and talks to another point.

Seeing this diagram made me question why, if content is so easily spread, on my own SNS (social networking sites), the statistics aren’t growing at a rapid rate. I began to hypothesise how I could increase the breadth and reach of my network. If media products have now become ‘transmedial’ as the text argues, the 360-degree programming shouldn’t only apply to TV text transforming into an online life, but also the interaction between SNS and the clear network linkages that are appearing between them. Network growth is participatory, So then, If the SNS are the specific nodes or ‘stops’ on our diagram above, I need to work out how can I use the internet pathways to navigate traffic between them.

The texts suggests this can be done with Imagery and I believe it can be accelerated by incorporating call to action buttons into or near the content. Images can be placed within blogs or articles (collaborative or self made) that are networked though in-text hyperlinks, recommendations to similar articles through google ad sense (also a paid promotion) and incorporating the use of social media buttons are all techniques that can help me to encourage traffic to land on my SNS pages. Another thought is, each platform and engine handles images in distinct ways, thereby revealing platform-specific technicalities. So, I need to use an approach attuned to the medium which I am sharing my content on.

Images shouldn’t be studied separately from their network. We may need to study how images circulate, are engaged with, appropriated, made into memes and changed over time. visual vernaculars as having distinct visual patterns and practices for different platforms.

On Instagram images circulate via an algorithm that is adjusted and manipulated depending on how other SNS profiles interact with your content. The visual patterns on Instagram are vital for powering successful interaction on you profile. I have noticed my best interactions come from images that possesses all of these qualities;

1. An image that follows good photo composition
2. An image that has it’s own style and interacts well with the other images you have shared
3. An image that gives value to viewers- the need to learn something or their ideas need to be re-enforced
4. An image that subscribes to a particular niche
5. An image supported by text that inspires or excites readers

Lastly let’s talk about the results from my experiment this week. Although my follower-ship improved, it still wasn’t a huge growth. Using paid promotion and other Instagram affordances did change interaction rates, however people still chose not to follow or share my content.  Some weekly goals I’ll consider are:

1. To engage with the network, images, links and inter-site interaction to analyse how user activity evolves.
2. To create platform specific content and see how the interactions between SNS sites change.

 

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References-

Lister, M et al 2009, New Media: A Critical Introduction. Routledge, New York. (Sections: Networks, Users and Economics pp 163-169; Wiki Worlds and Web 2.0 pp 204-209; The Long Tail pp 197-200; User-generated content, we are all users now pp 221-232.)

Niederer, S 2018, Networked images: visual methodologies for the digital age. Amsterdam University of Applied Sciences, Amsterdam. (read pp.1-20)

Si Leong, E 2020, ‘Week 3 The Network’ PowerPoint slides, COMM2219, RMIT University, Melbourne.