how much do online writers make

how much do online writers make

Exploring the Earnings of Online Writers

1. Introduction to the Online Writing Industry

In the general professional writing industry, rates of pay are very sensitive to the amount of education in writing and to experience level. The relationship between pay and experience exists in Fiverr data, which reports the amount of experience a worker has in the gig description, but PayScale.com reports wages for other IT-related occupations held by college graduates range from $40,000 to $150,000 in 2010. Issac reported a content writer with 10 years of experience and a graduate degree in journalism might expect to earn $75/hr. Johnston reported that experienced ghostwriters for celebrities and journalists can earn six-figures per book, while Payne reports anonymous writers making $350-400 per week working alone. Since a writer who has successfully published a manuscript has a second profession to list on their resume, we expect manuscript publication to be a significant contributor to writer pay. Surveys have anecdotally found that directly paid commissions are often difficult to obtain for the growing freelance segment of online gaming writers and the skilled writers primarily write for free, volunteer, or accept donation. The highest scores for the quality of the producing organization’s content are primarily ones that focus on content dissemination.

Online freelance writing may not be extensively studied, but it has been around for a long time and is an important component of micro-work. There is a tremendous amount of variation in the rewards for participating in online freelance writing, and yet researchers know little of this variation. Freivalds and Kumar surveyed 530 U.S. online freelance writers in 2010 and found between 2 and 85 percent of their income came from online freelance writing. They found 30 to 40 percent of those working as writers do so for the love of writing. Twenty percent of the writers earn less than 25 percent of their income from online freelance writing, a third earn 25 to 75 percent of their income from writing, and 42 percent earn more than 75 percent of their income writing. While a few earn a good living at it, most earn relatively low wages. Three other surveys of online freelance writers report similar findings. Pan writes that some workers for Amazon Mechanical Turk perform tasks that are similar to content production and are paid as little as $0.01 per task. Kreutzer writes that median pay on the website Constant Content is $65.08 per submission and $15.02 for U.S. writers on Demand Media Studios.

2. Factors Influencing Online Writers’ Earnings

Model: Due to this fact, we employ the multiple linear regression model to explore which factors are significant to writers’ and writings’ earnings. Following that spirit, we modify the author’s number of making by allowing the level to affect authors’ earnings and the difference of writers’ performance. We characterize the level of a random writer i, of an economic variable ik on the writer’s, which is supposed to make effect on the writer’s earnings. i’s level; paper number k written by this author; and observation period t. Specifically, as authors and their written artifacts are present, our analysis has included pieces of writing, page clicks of writing, and page clicks of a single month. Given these circumstances, we would benefit from a method to estimate earnings that incorporates these key dimensions.

Data process and question selection: To fulfill our analysis, we collected both authors’ and writing’s detailed information, including their level, written writing piece information, and page clicks, readings, recommendations, and total number of eating events in the whole referring website. All the analysis time period is from February 20, 2007, to April 30, 2007, and the data represents all authors and their written artifacts which have been published.

In this section, we will firstly discuss the data processed and question selection in our analysis, and then introduce the four models. At last, we will denote the analysis’ factors influencing authors’ earnings results.

Our essay attempts to explore the factors that influence the earnings of online authors, based on 10-week data that have been collected from the largest Chinese online writing platform, Mushidun Website. The empirical results have shown that writers, writing type, pieces of writing, page clicks of writing, and page clicks of a single month are all significant influential factors.

3. Popular Platforms and Opportunities for Online Writers

Until now, most studies of freelance writers’ income, work quality, and job characteristics have relied on a single survey of members from The American Society of Journalists and Authors, the late-great Freelance Writer’s Report Card, and a series of salary reports for Cuba’s Cuban Writers and Artists Union and its members. Most scholarly investigations of the earnings of platform-mediated writers have centered on broad samples of adults who use the Internet as a general-purpose tool. Topics include the determinants of income, customer satisfaction, pricing strategies, paid writing behavior, the professionalism of entrepreneurial activities, and the role of commitment and gender in customer satisfaction. Faiella and Faiella offer a comprehensive literature review.

The platforms on which online writers generate income are rapidly expanding as a result of trends like the “information revolution” and business model innovations. Consequently, platforms’ earnings prospects have been examined by a vast number of researchers. Amazon Mechanical Turk (MTurk) is a common setting for experimental studies, along with Fiverr and Upwork, with MTurk attracting the highest level of attention. Kucher’s brief online survey generated an extremely detailed and comprehensive listing of Internet-mediated platforms for work, written in English, and featuring business models, client/customer locations and requirements, and statistical (if available) aggregated data. More recently, Schneider et al. have concentrated on platforms that primarily engage independent workers rather than salaried employees or speech labor, focusing on Europe. Instead of using targeted searches, they focus on the domestic markets of different European countries during searches and reports. Other authors, often of papers posted in disciplines like Engineering and Business, provide tables of platforms.

4. Strategies for Maximizing Income as an Online Writer

The results suggest that earnings are lower when writers have fewer choices about which jobs to accept, when they are not paid in full for their services or their copyright-protected work, and when their work is sold in very small units. Conversely, they also suggest that becoming an expert improves earnings, regardless of whether writers are employed by content mills, online worker platforms, or working independently. While this industry now employs many writers, relatively few earn more than a small amount, although earnings are fairly evenly distributed, so there are almost as many relatively high earners as there are very low earners. To help writers bridge the gap between writing time and earnings, online content platforms should help overcome some of the constraints.

The data described in this paper suggest that thin pickings are common in the online freelance writing industry. Few workers earn much money from this activity, and mean and median earnings are very low. Writers for content mills tend to earn the lowest amounts, but there is not a huge difference between mean and median task-related payments in any of the groups. These earnings are incredibly low given the nature of the tasks and the fact that many writers are well-educated and potentially capable of earning more elsewhere. Lowering the costs of search and communication should make it easier for workers to find the jobs that best fit their skills. To help bridge the gap between writing time and earnings, in a larger company structure that paid more and provided more stability, two dedicated roles led to increased earnings from this sample of workers – analyst and manager.

5. Conclusion and Future Trends in Online Writing Earnings

Our experimental study has a number of clear limitations. First, the sample size is small, which might affect the validity of the study. However, explorative and descriptive evidence on such a unique but pivotal profession is usually limited due to the lack of appropriate representative data sources. Second, although increasing in efficiency and decreasing the fixed costs of participation, broader generalizations on the determinants of online writers’ earnings are only possible by conducting a similar study on other important online writing sites or by directly surveying a wider and more generalizable fraction of writing communities of multiple platforms. Third, also depending on the limited size of our sample, so far we have only focused on the earnings of current Active Participants on the Mechanical Turk platform. These users’ decisions to participate in mobile writing are endogenous and likely affected by bidding earnings and the policy of Amazon’s Mechanical Turk, as well as selection effects that might induce a “treatment effect bias”.

The current chapter has provided an overview of what the earnings of online writers usually look like. The earnings figure is subject to substantial uncertainty, as the study has been conducted in an experimental setting, in order to analyze the entire distribution of earnings. This method is useful in order to identify, control, and measure the effects of some key determinants on online writing earnings, both at the bottom of the distribution of earnings, where quantile regression models can introduce and explore significant differences with OLS, and at the top of the earnings distribution with quantile regression methods.