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Online advertising is different from traditional advertising in several important ways, the most important of which relates with user data. On one hand it involves the collection of user data, and on the other the exploitation of the collected data.  The second important difference is how online advertising places messages in context that blur the lines of what is advertising and what is not. Examples of this include native advertising, advergames, and social influence campaigns. The third aspect has to do with how messages can be specificly tailored to maximize deceptiveness, even at a level of a single individual. Examples of techniques include micro-targeting, dynamic creatives and AI generated copy. These three aspects – data, messaging, and context – make up the three vectors on which offensive techniques can be excecuted by advertisers and their partners.

Online advertising marks an important point in the history of advertising; there is a notable shift in the society from accept-and-avoid strategies, to reject-and-prevent strategies. Most notable development highlighting this shift is ad blocking, and how more than 20% of internet users already use an ad blocker. Well implemented ad blocking effectively mitigates all threats on the data vector, and many threats on the messaging vector, but does not provide sufficient protection against offensive tactics that leverage the context vector. For example, an ad blocker would not recognize a social influence campaign, or advergame, and therefore would not be able to protect the user from those threaths. This reveals an important shortcoming in the online advertising threat landscape; advertisers and their partners have an upper hand over the internet users. If internet users, or segments of users such as children, increase defensivess on one vector, advertisers and their partners can simply invest more on the two others. 

TOTES Model addresses the gaps in invidual tactics such as ad blocking, by providing a comprehensive guideline for embracing reject-and-prevent strategies for the protection of children. When implemented correctly, the suggested behavior changes lead to a safer, more meaningful online experience for children. The guidance includes a comprehensive review of defensive technologies, and relevant literature, while providing evidence and reasoning for overcoming common arguments against adopting such strategies.

Table of Contents


An Overview of TOTES Model

What is TOTES based on

How researchers can use TOTES

1. Data

1.1. Motivations for Data Harvesting

1.2. Four Models of Data Harvesting

1.2.1. Data harvesting as a means to targeting advertisements

1.2.2. Data harvesting as a means to reselling it for revenue

1.2.3. Data as a means to harvest immaterial labour

1.2.4. Data as a means to harvest cognitive energy

2. Messaging

2.1. Demand Generation

2.2. Bernaysian Communications

2.2. From Broadcasting to Micro-Targeting

2.3. Examples of Deception by Messaging

3. Context

3.1. Pseudo Advertising

3.2. Apps

3.3. Games

3.4. Influencer marketing

3.5. Examples of Deception by Context

4. Why Defend Against Online Advertising

4.1. Why Advertisers Advertise

4.2. The Five Levels of Negative Effects

4.2.1. The negative effect on individuals

4.2.2. The negative effect on families

4.2.3. The negative effect on the society

4.2.4. The negative effect on nation-states

4.2.5. The negative effect on the internet

5. How to Defend Against Online Advertising

5.3. Adblocking as a defensive strategy

5.3.1. Ad blocking at a device level

5.3.2. Ad blocking at a houshold level

5.3.3. Ad blocking at a school level

5.4. Muting as a defensive strategy

5.5. Online anonymity as a defensive strategy

5.6. Media reading skills and media critisism as defensive strategies

6. Roles in Protecting Children from Online Advertising

6.1. The Role of the Child

6.2. The Role of the Parent

6.3. The Role of the Educator

6.4. The Role of the School

6.5. The Role of the Governement

7. Overview of Defensive Technologies

7.1. Current implementations

7.2. Future landscape and call for innovation

8. Overview of Literature

9. Common Arguments

Come back for full guidance in Q4/2017

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