01 - WHO IS X?
02 - THREAT OF ABSURDITY
03 - CASUAL VOYEURISM
ABOUT

CONSENSUAL DOXXING

To provide a glimpse into how our seemingly mundane actions online might have adverse effects on our lives, this project examines the multitude of assumptions that could be made about any individual based on their personal online data, through the example of producing a data analysis based on an individual known as X who agreed for their online activities to be recorded over the course of a week.

Through this exploration and a complimentary deep dive into the issue, this project hopes to encourage a shift in mindset towards the need for more data privacy from consumers.

more about the designer: kiNLIN.XYZ
BEHIND THE ART DIRECTION
IMAGE TREATMENT
The visual direction began with the perspective of being viewed by machines, which inspired the bitmap treatment of images. To enhance the notion of losing your identity to what is being perceived by these entities, the glitching or sweeping effect was used to manipulate these images. 

As transparency or the need to present “things as they are” is a core motivation of the project, all images used in the project are lifted directly from the recorded footage during the data collection, which consists of screen recordings of the subject’s phone and laptop activities. 

These images are then further manipulated into collages to mimic the loose perceptions that data brokers have of their subjects, hinting their relation to corresponding inferences but not truly representing the truth.
COLOUR TREATMENT & MOUSE MOVEMENT
The overall dark visual tone of the project seeks to jolt these readers to the urgency of the message, with the dominant colour red used not only as a symbol of danger/threat, but also to guide readers to areas that require their attention.

Additionally, the constant trail of red attached to mouse movement is intentional to make readers more aware and weary of their journey across the website, where every move taken can’t be erased and is permanently etched into this online experience.
TYPE CHOICE
The display typeface, Sonic, was chosen as its movement-like extended forms embody how rapid digitisation has made it hard for consumers to see past customised conveniences, therefore requiring those who seek the truth to metaphorically put in effort to understand the message behind what is being presented.

The serif typeface, Cirka, was chosen to express the danger of being intimate and surrendering our identity and essentially ourselves to these entities, as all of this data exchange is being done with consent, whether fully understood or not.

The sans typeface, Neue Machina, was chosen to complement the display typeface, with its geometric features serving as a more legible representation of the robot or machinery aesthetic.
LIBERAL HOMOSEXUAL
PRO-CHINA SUPPORTER
LIKELY TO PROTEST
NOT A TEAM PLAYER
MELANCHOLIC CONSUMER
DISCOUNT SHOPPER
MENTALLY UNWELL
NIGHT OWL

ASSUMPTION

01

LIBERAL HOMOSEXUAL

BASED ON SOCIAL MEDIA ACTIVITY
SCROLL
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UNDERLINE
TO INTERACT
POST LIKED ON INSTAGRAM
@DEsiGNERS
HUMOR
@RICONASTY
@KELLEY
CHENG
@LARSLALA
@LAINA
RAUMA
@SUPERNOR
-MAL.SPACE
@MANESKIN
OFFICIAL
@MEI-
CROSOFT
@BITCH
@VICDE-
ANGELIS
@LILNASX
@MILEY
CYRUS
@ASIANFEED
@MLOUYE
@LILCAS
-PERV2
@MOTHER-
SHIPSG
@HIGHNUN
CHICKEN
@BRIAN
IMANUEL
@ACNH CUPID
@HAIKINI
@FISHBALL
ISHERE
@USHIKIMA
@STUDENT
DESIGN
@YKAAR
@PLASTIKA
FANTASTIKA
@WAKEUP
SINGAPORE
@JAPAN
LEADERS
@PANNLIM

X is a young, single homosexual female who has few friends.

X is liberal & artistic, spontaneous, but also shy & reserved, neurotic and competitive.

Even though the subject does not seem to be very active on social media, the posts “liked” by the subject on Instagram has the potential to reveal their “sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age and gender” (Kosinski et al.), according to a published study based on analysing Facebook “likes” of 58,466 volunteers from the United States.

While the algorithmic tool to determine this is unavailable for this project to utilise, based on the list of “most predictive ‘likes’” (Kosinski et al.) detailed in the study, there are correlations with the subject’s “liked” posts, therefore the following inferences could apply to the subject.
Total Visits to
Social Media
Applications (SMA)
LEGEND
INSTAGRAM
YOUTUBE
REDDIT

X is most active on the online platform YouTube but is not a Heavy SMA User.

Their average time spent on SMA is 02:13:00 as compared to heavy SMA users who spend an average of 4 hours per day.
54
DAY 1
129
DAY 2
268
DAY 3
108
DAY 4
51
DAY 5
185
DAY 6
150
DAY 7
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POSSIBLE DANGERS
When matched with third-party (data brokers) databases, such as websites visited, newsletters received, and purchase behaviour both on and off the Internet, these inferences could be aggregated with information from others whose habits are similar. From there, groups are defined with any consumer who have similar traits and interests, and are then sold to marketing firms who purchase these social networking profiles in bulk in order to develop their marketing campaigns (Payton & Claypoole 85; FTC 19).

Other than to benefit advertisers alike, sensitive information such as the inferred sexual orientation of the subject could be used against them, accurate or not. As the researchers of the study warn, “One can imagine situations in which such predictions, even if incorrect, could pose a threat to an individual’s well-being, freedom, or even life” (Kosinski et al.). This is especially concerning if the individual is living in an environment that is not welcome to LGBTQ+ communities, as it could prove to be detrimental to their lives and even their families (Schep 82).
References
Federal Trade Commission. Data Brokers: A Call for Transparency and Accountability. Federal Trade Commission, May 2014. www.ftc.gov/system/files/documents/reports/data-brokers-call-transparency-accountability-report-federal-trade commission-may-2014/140527databrokerreport.pdf. Accessed 26 November 2021.
Payton, Theresa M., and Theodore Claypoole. Privacy In The Age of Big Data: Recognizing threats, defending your rights, and protecting your family. Rowman & Littlefield, 2014.
Kosinski, Michal, et al. “Private traits and attributes are predictable from digital records of human behavior”. Proceedings of the National Academy of the United States of America, vol.110 , no.15, 2013, pp. 5802–5805. doi:10.1073/pnas.1218772110.
Schep, Tijmen. Design My Privacy. BIS Publishers Ltd, 2016.

ASSUMPTION

02

PRO-CHINA SUPPORTER

BASED ON CHOSEN VIDEO ENTERTAINMENT
TOP 10 MOST WATCHED
YOUTUBE CHANNELS

X uses the platform YouTube as their primary source of video entertainment.

They watched videos on YouTube 98 times as compared to a total of 21 visits on other websites such as Twitch.com, 9anime.to and WatchCartoonsOnline.io.

In theory, from the Top 10 YouTube Channel list, X is inclined to lean politically towards pro-China ideals, as they actively watch content from the “South China Morning Post”, which has been reportedly increased in propagandistic written articles, on top of censorship felt by their reporters which can be seen as being politically aligned with the Chinese Communist Party (Hui & Li).
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X is most engaged with ‘Lifestyle’ genre videos.

31
‍
LIFESTYLE
29
‍
GAMING
19
‍
ENTERTAINMENT
16
‍
COMMENTARY
13
‍
ANIMATION
12
‍
COOKING
8
‍
COMEDY
7
‍
JOURNALISM
2
‍
MUSIC

1
EDUCATIONAL
PLAYS PORTION OF VIDEO
VS. PLAYS VIDEO COMPLETELY
LEGEND
SHORT-FORM VIDEOS
LONG-FORM VIDEOS

X prefers long-form content over short-form content.

Long-form content are videos that are 8 minutes or longer.

Combined with an understanding that X enjoys long-form content and particularly the Lifestyle genre, in theory if a combination of those two factors with specific political messages were in videos were promoted to X, they are likely to engage with them, especially since they have a 57.7% rate of engaging with content that is recommended by YouTube.

In fact, if the comment section were populated with comments with similar sentiment, it is likely to influence the subject as they read the comments section 30.5% of the time they are on the platform.
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POSSIBLE DANGERS
Being able to keep the subject’s attention on the platform is crucial, as supported by other video streaming services such as Netflix, who view their main competitor as people’s need to sleep instead of traditional competitors (Hern). With more time spent, the likelihood of advertisers willing to invest in the platform will be higher as well, therefore all these factors build up a personalised profile of the subject and expose what kind of content is likely to influence their decisions.

As Véliz, an academic and critically-acclaimed writer on digital ethics cautions, by collecting and learning through our personal data, corporations such as Google (who owns YouTube) gain power to decide what is considered knowledge about us, whether or not it is outdated or out of context (Véliz 60).
With this knowledge, not only could data scientists cater advertisements to you, they could nudge you towards taking political sides that are evident from their analysed data about you. Take the Cambridge Analytica case as an example. Using their algorithms based on data extorted from Facebook users without their consent, they were able to develop psychological profiles of these users and manipulate their feed to influence their votes for political parties and referendums, using tactics such as targeted fake news, misinformation, fear mongering, and more to encourage polarized views amongst citizens (Wylie; Cadwalladr & Graham-Harrison).
References
Cadwalladr, Carole and Emma Graham-Harrison. Revealed: 50 million Facebook profiles harvested for Cambridge Analytica in major data breach. Guardian, 2018. www.theguardian.com/news/2018/mar/17/cambridge-analytica-facebook-influence-us-election. Accessed 26 November 2021.
Hern, Alex. Netflix's biggest competitor? Sleep. Guardian, 2017. www.theguardian.com/technology/2017/apr/18/netflix-competitor-sleep-uber-facebook. Accessed 26 November 2021.
Hui, Mary and Jane Li. China’s crackdown on Jack Ma has come to Hong Kong’s paper of record. Quartz, 2021. qz.com/1985102/chinas-crackdown-on-jack-mas-alibaba-reaches-hong-kongs-scmp/. Accessed 26 November 2021.
Véliz, Carissa. Privacy is Power. Transworld Publishers Ltd, 2020.
Wylie, Christopher. Mindf*ck. Inside Cambridge Analytica’s plot to Break the World, pp 110-115. Penguin Random House, 2019.

ASSUMPTION

03

LIKELY TO PROTEST OR DISSENT

BASED ON ENGAGED ARTICLES AND VIDEOS
ISSUES OF INTEREST
LEGEND
DEMOCRACY
DATA PRIVACY
racism
environmental pollution
death penalty
We’ve Pretended About Taiwan for
72 Years. It May Not Work Any Longer.
SpaceX drops Zoom due to
‘significant’ privacy concerns
Science debunks a racist
myth about Chinese food
Call on F45 HQ to look
into this @F45_training
Sunday Read - Gumbo Media:
Reclamation and Reimagination
This one is for all the nature
andenvironment lovers
Game Theory: You KILLED the Planet!
(Subnautica) #TeamSeas
We Cleaned The Beach #shorts
#unfckit challenge #TeamSeas

NNT - #SaveNagaenthran

X is most concerned with issues of Racism and Environmental Pollution.

Beyond curbing advertisements for products or services that are in line with the views of the subject, such as brands which promote environmentally-friendly practices or conscientiously taking action against racism, knowing what kind of issues people are concerned about is also of interest to employers and governments.

Other than combing through social media to understand if there are any mishaps or socially unacceptable practices that their potential hire may have been involved in, companies are might also be interested to know if their workers will be someone who are willing to fight for their rights.

This is due to reported cases of companies going as far as to detail anti-racism campaigners, environmentalists, those who raised health-and safety concerns, political activists and more, as exemplified by the 30-year undercover exposé on UK’s building firms that blacklisted union members across 16 years (Smith & Chamberlain).
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POSSIBLE DANGERS
Similarly, but on a wider scale, governmental entities have been proven repeatedly to employ mass surveillance on its citizens, such as Edward Snowden’s leaks of top secret US intelligence documents describing the NSA’s massive collection of citizens’ phone and internet traffic data across telecommunications networks (Macaskill and Dance), or China’s Social Credit System (SCS) which  rates each individual citizens’ “trustworthiness” based on an algorithmic surveillance system to determine social and financial behaviour (Kotska 1588).

Thus it is not far-fetched to speculate that social issues that citizens are interested in, especially those that are against the interests of the government could be seen as unfavourable and these subjects could be labelled as dissident of the state, without them ever being able to correct these sensitive inferences themselves.
References
Kotska, Genia. “China’s social credit systems and public opinion: Explaining high levels ofapproval”. New Media & Society, Volume 2, Issue 7, 2019.
Macaskill, Ewen and Gabriel Dance. NSA Files: Decoded. Guardian, 2013. www.theguardian.com/world/interactive/2013/nov/01/snowden-nsa-files-surveillance-revelations-decoded#section/1. Accessed 26 November 2021.
Smith, David and Phil Chamberlain. On the blacklist: how did the UK’s top building firms get secret information on their workers?. Guardian, 2015. www.theguardian.com/uk-news/2015/feb/27/on-the-blacklist-building-firms-secret-information-on-workers. Accessed 26 November 2021.

ASSUMPTION

04

NOT A
TEAM
PLAYER

BASED ON LITERATURE READ
LITERATURE READ
LEGEND
COMICS
NON-FICTION LITERATURE

According to a study linking literature genre and empathy,
X is less empathetic than their counterparts as they do not partake in literary fiction.

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POSSIBLE DANGERS
The findings from the study showed that people who read literary fiction where readers are challenged to garner their perceptions about characters with complex emotions and perspectives, are more likely to be empathetic to others, as compared to those who read non-fiction, genre(popular) fiction or none at all (Castano & Kidd 4).

This could be valuable knowledge to employers who rely on these data inferences as a filter for potential hires (Véliz 63). Afterall, ensuring an environment where all employees are amicable and work well with each other involves proper communication and less empathetic individuals are less likely to pick up on social cues, be considerate or tactful, and as a result cause misunderstandings that disrupt workflow (Gentry 6).
References
Castano, David C. Kidd. Reading literary fiction improves theory of mind. Science, vol.18, no.342, 2013, pp.377-380. doi: 10.1126/science.
Gentry, William A. et al. Empathy in the Workplace: A Tool for Effective Leadership*. Center for Creative Leadership, 2017. cclinnovation.org/wp-content/uploads/2020/03/empathyintheworkplace.pdf. Accessed 26 November 2021.

ASSUMPTION

05

MELANCHOLIC CONSUMER

BASED ON MUSIC PLAYLIST HISTORY
music GENRES LISTENED
LEGEND
1
ROCK
4
dance/electronic
2
alternative/indie
5
pop
3
SYNTH-WAVE
6
R&B/SOUL

Due to the overwhelming majority of genre preferences in Alternative/Indie and Rock,
X is relatively open-minded, disorganised, neurotic, has little social interaction and is likely to be critical or aggressive.

X is also more likely to be in Urgent, Defiant, Brooding, or Somber moods during their listening sessions.

Similar to how “likes” were used to determine personality traits, music genres can be utilised to inform data scientists of the subject’s personality traits. According to a study by Spotify, their algorithm can predict users’ personality traits by analysing their musical preferences and listening habits with relatively high accuracy (Anderson et al.). Based on the study, the following inferences would apply to the subject.
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POSSIBLE DANGERS
Understanding users’ moods is important to Spotify as they have reportedly used this information to serve targeted advertisements according to the current mood that their listeners are in, after correlating with additional information such as where and when their listeners begin their listening sessions, along with any available third-party data (Peterson).

It seems that this could be an effective marketing strategy as a study researching the correlation between negative emotions, particularly sadness, and spending habits. The study concluded that individuals who are more self-oriented and feeling sad, are more likely to spend their money (Cryder et al.). Therefore, X who has little social interaction, neurotic tendencies and is mostly in negative moods during their listening sessions, is very likely to make purchases when they are listening to Spotify.
In fact, even banks such as the Bank of England, have been reported to monitor their clients’ Spotify behaviour on a nationwide scale in order to gauge the consumer sentiment at any period of time, and noted that other factors such as reading preferences, video entertainment and video games preferences could also help to assess consumer behaviour (Elliott).
References
Anderson, et al. “Just the Way You Are”: Linking Music, Listening on Spotify and Personality. Journal for Social Psychological and Personality Science, vol.12, no.14, 2020, pp.561-572. doi:10.1177/1948550620923228.
Elliott, Larry. Spotify trends could help us gauge the public mood – Bank of England. Guardian, 2018. www.theguardian.com/business/2018/apr/30/music-downloads-can-gauge-consumer-vibe-bank-of-england. Accessed 26 November 2021.
Cryder, Cynthia E. et al. Misery is not Miserly: Sad and Self-Focused Individuals Spend More. Journal for Psychological Science, vol.19, no.6, 2008, pp.525-530. doi:10.1111/j.1467-9280.2008.02118.x.
Peterson, Tim. SPOTIFY TO USE PLAYLISTS AS PROXY FOR TARGETING ADS TO ACTIVITIES, MOODS. AdAge, 2015. adage.com/article/digital/spotify-playlists-gauge-moods-ad-targeting/298066. Accessed 26 November 2021.

ASSUMPTION

06

DISCOUNT SHOPPER

BASED ON VISITS TO MERCHANTS
MEDIA CHANNELS USED
RELATED TO PURCHASE
LEGEND
Resulting in purchase
DIRECTED TO MERCHANTS
MAIL NEWSLETTER
GOOGLE SEARCHES
INSTAGRAM
YOUTUBE
LISTING VIEW COUNT
2
3
4
6
LISTING TYPE SCROLLED
LEGEND
ON-SALE
REGULAR-PRICED
CLICKS CTA TO LISTINGS
LEGEND
ON-SALE
REGULAR-PRICED
AFTER VIEWING LISTINGS
LEGEND
added to cart
not added to cart

The most effective media channel for X is Google Searches.

68.4% of the links were directed to merchant websites which resulted in 3 purchases.
On the other hand, Mail Newsletter was visited more often but only resulted in 1 purchase.

X is most likely to complete their purchase when they have viewed a listing a minimum of 4 times.

X likes to view Regular-Priced listings, but will only buy listings that are On-Sale.

X is therefore likely to be a Discount Shopper.

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POSSIBLE DANGERS
Over time, online merchants that X is a member of will be able to track the subject across their purchases and shopping habits, and determine the effectiveness of in-store promotions, curate certain styles or brands similar to their tastes, and level of brand loyalty.

They could also purchase third-party (data brokers) data about how specific consumers spend their money beyond their websites to gather a more comprehensive profile on their consumers. In fact, companies could recommend the subject with higher priced listings based on what they might be willing to pay for a certain range of products, the location where they stay, their preferred browsing channel, and even their nationality (Pedersen et al.).
References
Pederson, Katie, et al. How companies use personal data to charge different people different prices for the same product. CBC, 2017. www.cbc.ca/news/business/marketplace-online-prices-profiles-1.4414240. Accessed 26 November 2021.

ASSUMPTION

07

MENTALLY UNWELL AND UNDESIRABLE

BASED ON SEARCHES AND ARTICLE KEYWORDS
POSSIBLE HEALTH INTERESTS
BY KEYWORDS AND SEARCHES
LEGEND
SKINCARE
HEALTH INSURANCE
INFECTIONS
ALCOHOL

X is likely partaking in alcohol,
and shows signs of infections.

This could be indicative of multiple skin-related infections or poor hygiene practices. As such, X could be showing signs of depression, as a lack of personal hygiene is a result of lack of motivation towards everyday activity and a symptom of mental illness (Ferguso and Legg).
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POSSIBLE DANGERS
As alcohol is regarded as a form of self-medication by people coping with depressive symptoms (Faris & Legg), X could therefore be highly undesirable to health and life insurance companies and be charged a higher premium since regular consumption of alcoholism could cause a premature death (World Health Organisation).

Subsequently, calculations of health costs resulting from alcoholism and mental health treatment would affect hiring decisions of employers (Payton & Claypoole 167).
References
Faris, Stephanie and Timothy J. Legg. Recognizing Forms of Self-Medication. Healthline, 2018. www.healthline.com/health/depression/forms-self-medication. Accessed 26 November 2021.
Ferguson, Sian and Timothy J. Legg. Yes, Mental Illness Can Impact Your Hygiene. Here’s What You Can Do About It. Healthline, 2019. www.healthline.com/health/mental-health/mental-illness-can-impact-hygiene. Accessed 26 November 2021.
Payton, Theresa M., and Theodore Claypoole. Privacy In The Age of Big Data: Recognizing threats, defending your rights, and protecting your family. Rowman & Littlefield, 2014.
World Health Organisation. Alcohol. World Health Organisation, 2018. www.who.int/news-room/fact-sheets/detail/alcohol. Accessed 26 November 2021.

ASSUMPTION

08

NIGHT
OWL

BASED ON RECORDED TIME OF ACTIVITIES
ACTIVITY BY TIME
MORNING
(0500-1200)
AFTERNOON
(1200-1700)
EVENING
(1700-2100)
NIGHT
(2100-0400)
VIDEO ENTERTAINMENT
browsing
merchants
reading emails
reading comics
social media
reading articles
google search
listening
to music

X is most active at Night, from 2100-0400.

X is likely to browse merchant websites when using Spotify, as there is an overlap of activity during Evening and Night between “Browsing Merchants” and “Listening to Music”.

Therefore, we can infer that Spotify is an effective agent in urging the subject to purchase products, as 62.5% of purchases made were also during the Evening and Night.

X is also most susceptible to advertisements during the Afternoon.

They engage with the most number of media channels during that period of time.

X has a habit of reading literature during Morning and Night.

Observed from their reading activity across emails, articles and graphic novels.
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POSSIBLE DANGERS
As mentioned before, advertisers and companies alike collect and analyse our data across various mediums, whether it’s web-browsing or our mobile applications, to understand consumer behaviour and build precise consumer profiles, and with a timeline of these activities, they are able to improve their accuracy of these inferences (Doss 85).
References
Doss, April Falcon. Cyber Privacy. BenBella Books, Inc, 2020.

SO IS
THIS X?

As exhibited in this analysis, such unfounded assumptions established from unrestricted access to our data could result in real-life consequences that are unwanted and damaging.

However ludicrous, it is an unfortunate fact that because behavioural profiling companies or marketers believe that our online behaviours are intimately connected to our beliefs, opinions and our way of life, they will utilise these digital profiles of us to shape and influence us, whether we like it or not (Véliz 95).
NEXT CHAPTER
THREAT OF ABSURDITY

"As imprecise as the inferences may be, search strings often indicate something about our interests or our state of mind. Bad enough for data to intrude on the privacy of our activities and the state of our bodies; even worse for it to serve as some kind of mind-reading test.”

– Doss, former employee of the National Security Agency of USA and data privacy critic.