Authors

The constant exposure to negative media content has a significant impact on societies on a day to day basis. Our emotional and mental climate is largely influenced by the tone of voice and the content provided by medias (including social media). The way catastrophes, such as COVID-19, has been discussed in media and the extend of false and misleading information as well as fear inciting content has caused unprecedented anxiety and influenced negatively to human behaviour. The Tone of Voice Index (ToVI) helps consumers evaluate the type of content they are up against before diving in.

Unfortunately, for many media outlets the current model favours negative and polarised content and click-baits as they generate more advertising revenues, which in turn impacts nation's state of mind; the mental and emotional climate we live in and collectively share. It increases stress and anxiety, creates "us-them" dichotomies and conflicts, and decreases productivity and subconsciously impacts decisions making.

We have created a Tone of Voice Index (ToVI), an objective and easily understood score that helps analyse, assess, and rank medias according to their tone of voice and allows consumers to evaluate what type of content they are up against before diving in.

Our AI-powered index score is generated using Natural Language Processing (NLP) which is based on Machine Learning. Our tool analyses the text-based content produced by media outlets and generates an indexable rating, which is currently based on sentiment analysis that sorts the content into positive, neutral and negative. Later, the accuracy of the index is improved by analysing the content’s polarization (polarized – neutral), stance detection (title vs. content), emotional level and source critique.

The score helps identify responsible media outlets which will be given a Quality Label, a Badge of Responsibility. A database of quality labelled medias is created to help advertisers protect their brand value.

In the first stage the tool will be created for the end user to help them automatically evaluate the content of the visited site. Later the user will be able to set preferences regarding the tone of content they want to consume and giving them the opportunity to easily avoid content that is adversarial to them. This could ignite a counter movement where individuals are demanding to take control of their news feeds and consume content from quality labelled sources only.

Our second stage of the tooling will provide utilities to media outlets to steer their content creation and provide all users, even those without our tool, benchmarks regarding the tone of their content. It would resemble the Oiva –index https://www.oivahymy.fi/en/front-page in use by Finnish restaurants, giving consumers a quickly recognizable way to evaluate what kind of content they are up against.

The consumer consciousness creates a strong enough group and corporate responsibility pressure, altering the tone of voice of many global media outlets into a more responsible one. The sudden disruptive turn of consumers into the guiding force of the 500-billion-dollar advertising industry marks a completely new era. The rapidly changing landscape opens new data and responsibility driven business models.

In the final stages, as the index is widely acknowledged, it would be used by ad brokers and media outlets as a classifier for how ads (and revenue) is directed, steering content creation towards more positive and consumer friendly tone of voice.

Try It out

Hackathons

Technologies

api, naturallanguageprocessing(nlp), python

Devpost Software Identifier

259783