Bullying, harassment, violent content, hate, porn and other problematic content circulates on digital platforms. Who should be responsible for stoping the spread of this content and how?

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Introduction

 

From the emergence of APPANET (the predecessor of Internet) in the second half of the 20th century to the Internet today, the Internet has been in Spontaneous Order, where the Internet develops freely in a scale-free space, and gradually forms a unique order of its own. For example, many unintended consequences of myriad individual actions will bring a lot of damage to the Internet that cannot be avoided (Sack, 2018). Bullying, harassment, violent content, hate, pornography and other problematic content distribution on today’s digital platforms is a problem with a wide range of influences, which is one of the many unintended consequences of This is the concrete impact of many unintended consequences of myriad individual actions that make the Internet bring a lot of negative effects and great risks to the world. To address this issue of distribution, this paper will present more information about who is responsible for stopping the distribution of Bullying, harassment, violent content, hate, pornography and other problematic content and in what ways they should stop the distribution of these negative messages.

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There are three core components here, they are:

-The the government that can represent the law to control the Internet.

-The Internet companies that represent the Internet operators.

-The individuals whose lives are affected by the Internet.

The attitudes and actions they should have in the face of Bullying, harassment, violent content, hate, pornography and other problematic content are central to the argument of the article.

 

The government should be responsible

 

The government, as the law maker and enforcer, is responsible for the spread of online spam, and it is the government’s job to maintain the stability of society by efficiently resolving conflicts in society through law. The Florida “Don’t Say Gay” bill of 2022 caused a great controversy and hatred among Internet users in digital media, and the source of the controversy was the criticism of the “Don’t Say Gay” bill. Nowhere in the text does it say “gay” is correct. What this incident revealed was that the government was not strict in regulating much of the content and that the government’s efforts were not met with the expected response, which is an example of the government’s inability to make good laws to regulate speech. What the government should do is to enact more specialized laws for each of the different subsections of the issue, such as prohibiting certain words in public or in specified contexts. But the content of speech-based mandatory laws is often antithetical to the view of freedom of expression in international human rights law, and in order to avoid over-regulation and the opposite of higher-level and unambiguous laws (George, 2014), governments need to pay more to subdivide laws and complete more exclusive legal treaties with details for specific situations. Such laws would be more focused and complete, which would help eliminate the problem of unregulated online speech efficiently and quickly.

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The birth of unhealthy digital speech comes from netizens, and the circulation of such speech exists in digital platforms, and the government’s restraint on digital platforms needs to be synchronized to achieve better regulation. Unlike the early government’s lack of attention to Internet control, the rapidly developing Internet needs newer, faster and more comprehensive laws to manage, and the official and efficient enforcement of legal interventions will make it easier to regulate content and standardize behavior. The difficulty is that current online laws are not perfect, and when bullying, harassment, violent content, hate, pornography and other problematic content appear on online platforms, the government cannot guarantee to personally address these marginal behaviors in a short period of time, which leads to more negative information circulating in digital platforms. The government needs to designate more laws with accountability relationships to urge online platforms to self-manage and upgrade their security systems. Stricter government requirements on Internet platforms through data indicators will urge online platforms to be more active in improving data screening systems and management systems(Black, 2008), which will indirectly solve the problem of online speech regulation, and platforms will cooperate with the government to complete the regulation in digital platforms.

 

 

The Internet companies should be responsible

The social media operated by Internet companies is now the main platform for the circulation of hate speech. Internet  companies as platform managers have the obligation to maintain a healthy online environment,  and from many perspectives such as morality, professional ethics, social responsibility,  Internet companies must be responsible for stopping the transmission of bullying, harassment, violent content, hate, etc. porn and other problematic content. The first is the classical machine learning (ML) which is a mathematical linear algorithm, it can be used by simple surface features, word generalization, sentiment analysis, lexical resources, linguistic features, knowledge-based features, meta-information and multimodal information to detect linguistic features and thus flag hate speech ( Mullah & Zainon, 2021). The second one is the ML extension algorithm Deep Learning (DL) which can analyze nonlinear data and it builds analysis by artificial neural network (ANN) to find the deeper meaning of some signals, but it has the disadvantage that the technology is not mature enough. In order for ANNs to be more purposeful, they now need to do three things:

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The first is that Internet companies should build more diverse models that are compatible with ML and DL, and invest more R&D costs in DL. The new models could more comprehensively and quickly flag more potentially hard-to-detect hate speech which has deeper meanings or is intentionally hidden.

 

The second thing is that Internet companies should add more human oversight, which can do many things that algorithms can’t, such as language games and the ability to spot potential dangers.

 

The third thing is that the Internet should work with the government to implement the real-name system for Internet users, for example, by having Internet users submit materials to the government to authenticate their identities, and the government should assist Internet companies in the real-name system while ensuring the privacy of citizens.

 

 

The individuals should be responsible

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The individual represents the person whose life is affected by the Internet, and the source of negative information is the existence of the individual, so the individual has to pay the most responsibility for the interception of hate messages in the Internet. Individuals act as perpetrators, victims, and witnesses in the spread of hate messages, and their merger brings about the whole event from the creation of negative messages to the emergence of negative effects. daphne Keller (2022) argues that the huge gap between speech prohibited by social norms and speech prohibited by law leads to the emergence of hate speech on many digital media platforms. The negative speech that cannot be prohibited by law nevertheless violates many people’s sense of decency, morality, or justice. What each individual should do is to speak on the Internet with a sense of social responsibility and respect for others. Individuals need to respect and value Internet Law from the heart, not just rely on the protection of freedom of speech to vent their desires, which is a reflection of a lack of social responsibility. Using the law, morality and a sense of social responsibility to discipline oneself and give more care to those around you will have a positive impact on stopping the emergence of negative information on the Internet.

 

Conclusion

The future development of the Internet is immeasurable, and there are many relevant laws that need to be updated more quickly to ensure a more comprehensive reduction of the negative impact of the Internet on society. According to the current situation, the government, Internet companies and individuals should be responsible for blocking the flow of negative information and making changes together, so that the three parties can make progress together to make the Internet environment healthier, and a healthy Internet environment will bring better Internet benefits to society.

 

 

 

Reference List:

 

Black, J. (2008). Constructing and contesting legitimacy and accountability in polycentric regulatory regimes. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1091783

 

Freedom of speech in Australia. (n.d.). https://www.aph.gov.au/Parliamentary_Business/Committees/Joint/Human_Rights_inquiries/FreedomspeechAustralia

 

George, C. (2014). Hate speech law and policy. The International Encyclopedia of Digital Communication and Society, 1–10. https://doi.org/10.1002/9781118767771.wbiedcs139

 

Internet law: Everything you need to know. (n.d.). UpCounsel. https://www.upcounsel.com/internet-law

 

Keller, D. (2022, June 28). Lawful but awful? Control over legal speech by platforms, governments, and internet users. The University of Chicago Law Review Online. https://lawreviewblog.uchicago.edu/2022/06/28/keller-control-over-speech/

 

Lavietes, M. (2022, March 16). What Florida’s “Don’t Say Gay” bill actually says. NBC News. https://www.nbcnews.com/nbc-out/out-politics-and-policy/floridas-dont-say-gay-bill-actually-says-rcna19929

 

Luban, D. (2020). What Is Spontaneous Order? The American Political Science Review, 114(1), 68–80. https://doi.org/10.1017/S0003055419000625

 

Mullah, N. S., & Zainon, W. M. N. W. (2021). Advances in machine learning algorithms for hate speech detection in social media: A review. IEEE Access9, 88364–88376. https://doi.org/10.1109/access.2021.3089515

 

Sack, H. (2018, January 1). How the ARPANET became the Internet. SciHi Blog. http://scihi.org/arpanet-became-internet/

 

Seker, E. (2020, September 16). Artificial neural networks (ANN). Towards Data Science. https://towardsdatascience.com/artificial-neural-networks-ann-21637869b306

 

The Internet real-name system. (n.d.). CustomWritings. Retrieved October 14, 2022, from https://customwritings.co/the-internet-real-name-system/