LOVE.LANGUAGE

Investigating how love is communicated from a digital standpoint.

LOVE.LANGUAGE is an experiment which involves photo and screenshot analysis by visually arranging all media that I have interacted with online (both sent or received) over time into a grid. Parameters were set when arranging these photos such as time sent/received and the type of media. 

The final showcase of this particular experiment focused on the idea of a digital love language—how this can be communicated through sharing photos. By arranging the photos and identifying each food photo, I was able to concurrently visualise how much I communicate feelings with food in the digital space.

To visually present these findings, each food related media was highlighted by replacing them with white squares. This is made interactive where each square reveals what that particular photo entailed when hovered over.

LOVE.LANGUAGE pushes the boundaries of what a love language can be, and enabled me to make sense of how I express affection and the nuanced actions I take to connect with others online. 

FREQUENT.WORDS

An exploration of how choices of unique words change over time.

Methods involved in FREQUENT.WORDS include data mining and word analysis where code is utilised to find out the most used words when I message others online. These data minings were also conducted several times to explore how these findings would change under different time periods.

This is visually presented with a list of words along with the number of times they appear in my online conversations in chronological order.

An individual’s choice of words serve as indications of their character. By analysing my use of words over time, I was able to witness how I have developed as a person over time. These changes included a rising trend in word length, and words with strong emotive connotations.

HAPPY.BIRTHDAY

Unearthing the intention behind each Facebook post.

Applying a similar methodology to Daniel Clark’s Tech and me, HAPPY.BIRTHDAY investigates the authenticity behind Facebook posts, and the changes in content that is posted over time.

When investigating my Facebook posts, a staggering number of birthday posts had appeared. The method of close reading* was used to highlight the amount of times I had posted a ‘generic’ birthday post that could’ve been addressed to anyone. This analysis involved laying all of my posts into one space, and connecting each birthday post with a line to generate a visual pattern.

This is visually portrayed by having each white dot signifying a birthday post, with lines interconnecting each one. This puts into perspective the rise in generic posts over time, raising conversations about interaction with others online and the gradual shift in the use of public social media.

*CLOSE READING:
“Thoughtful, critical analysis of a text that focuses on significant details or patterns in order to develop a deep, precise understanding of the text’s form, craft, meanings, etc.” Beth Burke — A Close Look at Close Reading (n.d.).

TRACK.RECORD

Unveiling the emotive states of each message sent online.

Using a similar process as FREQUENT.WORDS, TRACK.RECORD measures the emotive states of each message I’ve sent and received across three close friends. Through code, a sentiment analysis* was conducted, where a value between -1 to 1 (negative to positive emotion) is determined for each message. 

This data was further experimented with through data visualisation, where one of the iterations was chosen to portray the information.

TRACK.RECORD was an experiment which prompted self-reflection on the states of my personal friendships, and how I portray myself towards different people online—I particularly found the stark contrast in polarities between two people very jarring, where one relationship had very consistent values, and and the other having many extreme values.