Policy-making is driven by the need to solve societal problems and should result in interventions to solve these societal problems. Examples of societal problems are unemployment, pollution, water quality, safety, criminality, well-being, health, and immigration. Policy-making is an ongoing process in which issues are recognized as a problem, alternative courses of actions are formulated, policies are affected, implemented, executed, and evaluated. This process should not be viewed as linear as many interactions are necessary as well as interactions with all kind of stakeholders. In policy-making processes a vast amount of stakeholders are always involved, which makes policymaking complex. (Marijn Janssen, 2015)
Policy implementation is done by organizations other than those that formulated the policy. They often have to interpret the policy and have to make implementation decisions. Sometimes IT can block quick implementation as systems have to be changed. Although policy-making is the domain of the government, private organizations can be involved to some extent, in particular in the execution of policies. (Marijn Janssen, 2015)
The Availability of Big and Open Linked Data (BOLD)
Policy-making heavily depends on data about existing policies and situations to make decisions. Both public and private organizations are opening their data for use by others. Although information could be requested for in the past, governments have changed their strategy toward actively publishing open data in formats that are readily and easily accessible (for example, European_Commission 2003; Obama 2009). New applications and innovations can be based solely on open data, but often open data are enriched with data from other sources. As data can be generated and provided in huge amounts, specific needs for processing, curation, linking, visualization, and maintenance appear. The latter is often denoted with big data in which the value is generated by combining different datasets. Current advances in processing power and memory allows for the processing of a huge amount of data. BOLD allows for analyzing policies and the use of these data in models to better predict the effect of new policies. (Marijn Janssen, 2015)
Once all things are ready and decisions are made, policies need to be executed. During the execution small changes are typically made to fine tune the policy formulation, implementation decisions might be more difficult to realize, policies might bring other benefits than intended, execution costs might be higher and so on. Typically, execution is continually changing. Evaluation is part of the policy-making process as it is necessary to ensure that the policy-execution solved the initial societal problem. Policies might become obsolete, might not work, have unintended affects (like creating bureaucracy) or might lose its support among elected officials, or other alternatives might pop up that are better.(Marijn Janssen, 2015)
Social media has taken over the world. Almost every person is using social media today either through their Smartphone, computers or other portable devices. This raises the question of how social media can be used to influence policy to solve the issue of unemployment among the youth. Studies show that sixty percent of young people in developing countries are unemployed. A good example of this is Africa where youth population is growing exponentially. Policy making is a process that is affected by various economic and social factors. Social media can play a significant role in shaping the social sphere where policies are developed (Panagiotopoulos, Bowen & Brooker, 2017).
Through social media, people learn how certain policies will affects them. The government also gets feedback and suggestion of how to improve their policies .The young people can use social media to send suggestions how policies that can help reduce joblessness. Young people can also offer policy recommendation to the government that allow them to conduct some business creating employment opportunities. Since the government has official social media sites, it is easy for their feedback to get assimilated in the process of developing policies. Youth representative in the government can then spearhead such suggestions to be incorporated in policy.
The rapidly changing social media data can be used to track behaviors and attitudes of people towards reducing unemployment. While governments have put I efforts to determine the rate of unemployment, data has always been inconsistent and this affects policy making. Social media is well positioned to fit this. Data obtained from social media can be used to determine the number of unemployment and whether people share the same perspectives about unemployment (McDonald & Thompson, 2016). This is because social media offers a wide range of data that can be harnessed to develop policies focused on reducing unemployment in the society.
There are various areas of employment policy where social media can provide insights and suggest certain policy implementation. For example, social media can provide locations of most unemployed youth. This will help the government to develop policies considering such areas. The numerous social media platforms and their inherent analysis techniques provide a way in which it can track indicators related to policy. This can save a lot of financial resources and time for to governments to develop policies aimed at addressing joblessness among the youths (King, Schneer & White, 2017).
Policy makers normally rely on new data collection to determine the effectiveness of newly implemented policies. Comprehensive information about the policy effectiveness can be waited for a long period of time. This can delay follow up efforts for years. However, early indication on the social media about the trends in the market and the rate of unemployment could provide policy makers with insights for timely interventions. Since social media postings are frequent, the content posted is timely. In addition, people mostly post from mobile phones significantly contributing to frequency and immediacy. If these data is taken together, it can help policy makers develop policies that could reduce unemployment.
Policymaking processes are not often straightforward, however, and perception how pleasant to share their know-how with decision-makers can be difficult for scientists. Our Policy Guides intention to enhance conversation between our members and policymakers, make bigger they have an impact on of ecological research and support evidence-informed policymaking
A holistic strategy to policymaking in the digital age
Economies, governments and societies throughout the globe are going digital. About half of the world’s populace is now linked to the Internet, up from 4% in 1995. In many countries, digital transformation is now characterized through almost standard connectivity, but also through ubiquitous computing, and attracts on the generation and use of considerable amounts of data.
Technologies proceed to increase (Elkin-Koren, N., & Salzberger, E. M. 2013). rapidly and are combining in novel and progressive ways, pushing digital transformation in new and often unpredictable directions. Together, governments and stakeholders must shape a frequent digital future that makes the most of the significant opportunities that digital transformation holds to enhance people’s lives and raise financial boom for nations at all degrees of development, while making sure that no person is left behind.
Since digital transformation is transversal, the policy response needs to be holistic. Digital transformation affects many factors of the financial system and society in complex and interrelated ways, challenging current policies in many areas. As a result, silos are disintegrating, and challenging borders are becoming much less relevant. This means that more advantageous co-operation and collaboration are critical, as well as a re-think about how coverage is developed and implemented.
In particular, a flexible, forward-looking and built-in coverage framework that cuts throughout coverage silos is critical to ensuring a coherent and whole-of-government approach to fully recognize the doable of digital transformation and tackle its challenges. Under the auspices of the OECD’s Going Digital project, the OECD is creating such an integrated coverage framework. It consists of seven building blocks Access, Use, Innovation, Trust, Jobs, Society and Market Openness that are supported via quantitative symptoms and realistic policy guidance.
Not solely do governments want a built-in policy response to digital transformation, they ought to also seize the probability to go digital themselves. (Eberle, J., Lund, K., Tchounikine, P., & Fischer, F. 2016). Governments at the local, regional and national stages can use digital applied sciences to enhance affectivity and targeting, enable modern coverage format and rigorous have an impact on evaluation, and make bigger citizen and stakeholder engagement.
The OECD companion session at ITU Telecom World 2018 Going Digital:
An built-in and nice strategy to policymaking in the digital age will existing the OECD built-in policy framework and invite a panel to debate how to make insurance policies in the digital age greater coherent and fantastic by the use of digital technologies. This is critical, because the use of digital applied sciences now not solely drives market dynamism by using enabling innovation and new business models, but it additionally has the possible too seriously change how coverage is made and how governments interact with their citizens. This panel will be a chance to hear first-hand what governments are doing as they go digital.
Elkin-Koren, N., & Salzberger, E. M. (2013). The law and economics of intellectual property in the digital age: the limits of analysis. Abingdon, Oxon: Routledge.
Eberle, J., Lund, K., Tchounikine, P., & Fischer, F. (2016). Grand challenge problems in technology-enhanced learning Ii: MOOCs and beyond: perspectives for research, practice, and policy making developed at the Alpine Rendez-Vous in Villard-de-Lans. Cham: Springer.
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