In Australia, the news about the news is not good. In early March 2020, newswire service the Australian Associated Press announced it would be shutting down its operations after 85 years. 'Investors look to salvage parts of AAP as newswire faces closure', reported the Sydney Morning Herald on March 2 ( Samios 2020) . The Australian Broadcasting Corporation (ABC) predicted that 500 people would lose their jobs as a result (Khadem and Pupazzoni 2020) . In the US, the news about the news is just as bad, if not worse. 'On a rough day for American newspapers, investors arent buying Gannetts story and Tribunes not done chopping' was the headline on a Nieman journalism Lab story published on February 27 (Benton 2020) . According to the report, layoffs looked likely at the countrys No. 1 and No. 3 newspaper chains, while the countrys No. 2 chain (McClatchy) had already declared bankruptcy a fortnight earlier. As the Nieman Lab notes:
The Internet has brought forth an unprecedented flowering of news and information. But it has also destabilized the old business models that have supported quality journalism for decades. Good journalists across the country are losing their jobs or adjusting to a radically new news environment online (Nieman- Lab 2020) .
Is journalism in crisis? A wealth of research in Australia, the US and comparable countries suggests yes. Profits are hard, if not impossible, to come by; many firms are struggling or collapsing; and layoffs and redundancies are the norm. As Fenton (2011) wrote in a paper centred on the UK, 'News media are in crisis. The crisis is being managed by closing papers or shedding staff [and] these cuts are having a devastating effect on the quality of the news.' That was nearly a decade ago. Since then, the situation has only worsened. In Australia, the commonly cited figure based on research by the journalists union is that 3,000 journalism positions have been lost since 2011 (Ricketson et al. 2020) . For instance, it is estimated that in 2011 news publisher Fairfax Media employed about 1,000 editorial staff across the Sydney Morning Herald, The Age, The Australian Financial Review, and its Sunday papers, The Sun Herald and The Sunday Age. By mid-2017, however, half of those jobs were gone (Zion et al. 2018) , including the job of one of this papers authors. And then the coronavirus wielded its scythe. As we discuss below, the impact of COVID-19 on journalism jobs is proving devastating, with widespread job losses, particularly in regional areas (Crerar 2020) .
This research aims to assess the extent of the claimed 'journalism crisis' in Australia by analysing labour market data from 2012 to 2020. Our findings confirm that there is a crisis in journalism; a crisis that is now in full bloom due to the coronavirus pandemic. However, the data also yields more granular findings, including several surprises. One finding is that advertised journalism jobs only started to decline from 2016, not before. A second is that as the journalism jobs market becomes more volatile, gender inequity is worsening: women journalists who remain are younger and worse paid than the men who remain. And a third is that according to our skill similarity calculations, generalist 'Communications', 'Public Relations', and 'Social Media' are skills that are becoming more important to journalism, as opposed to traditionally specialist journalism skills such as 'Reporting', 'Editing', and 'Investigative Journalism'. These findings, together with others, reveal that the crisis in journalism is not only real, but in some ways more concerning than was previously understood.
To fulfil this research aim, we analyse a range of longitudinal data sources from job advertisements (ads) and official Australian employment statistics. The breadth and detail of these data provide us with the opportunity to comprehensively assess the journalism jobs market in Australia and how it has changed. We apply Data Science and Machine Learning techniques to analyse how the underlying skills of journalists in Australia have evolved. This allows us to build a data-driven methodology to determine which are the top journalism skills per year and identify the occupations in possession of these skills. Finally, we use these skill-level results to determine where people with journalism skills are likely finding alternative career paths.
The main contributions of this research include:
• providing a comprehensive and longitudinal assessment of journalism jobs in Australia from 2012 to 2020 by analysing both job ads data and occupational employment statistics;
• implementing a data-driven methodology to explore the nature of the oft-cited 'crisis' in journalism jobs in Australia,;
• applying this data-driven methodology to tease out more granular and specific trends in journalism jobs, including the impact of the current coronavirus pandemic, the contrasting impacts on regional and urban journalism jobs, and the gendered nature of ongoing impacts; and
• analysing the data to identify the skills sought in journalism jobs, and where people with journalism skills are likely finding alternate career paths.
Journalism jobs in crisis. If there is a crisis, the simple explanation is the Internet. (Putting aside COVID-19, to which we will return.) While digital channels have given journalism bigger audiences, they have also strangled income. Once, advertising funded journalism, but now advertising has largely migrated online. As the Australian Competition and Consumer Commission (ACCC) found in 2019, in the Final Report of its Digital Platforms Inquiry, 'The reduction in advertising revenue over the past 20 years, for reasons including the rise of online advertising, appears to have reduced the ability of some media businesses to fund Australian news and journalism'. The ACCC cited Census data showing that 'from 2006 to 2016, the number of Australians in journalism-related occupations fell by 9% overall, and by 26% for traditional print journalists (including those journalists working for print/online news media businesses)'. Further, the ACCC cited data provided by leading media companies showing that the number of journalists in traditional print media businesses fell by 20% from 2014 to 2018 a time of growth for Australia's population and economy (ACCC 2019). However, the pressures on news media are not spread evenly. For instance, local news is bearing a particular brunt. Between 2008 and 2018, 106 local and regional newspaper titles closed across Australia, representing a 15% decrease in the number of such publications. As a result, 21 local government areas previously served by a newspaper were now without coverage, including 16 local government areas in regional Australia (ACCC 2019). These figures are mirrored in the US. In 2018, Abernathy (2018) from the Hussman School of Journalism and Media at UNC released a report, 'The Expanding News Desert', which found that the US had lost almost 1800 papers since 2004, with 7112 remaining (1283 dailies and 5829 weeklies). This means that the US lost roughly 20% of its newspapers between 2004 and 2018. These closures included large dailies such as the Tampa Tribune and the Rocky Mountain News, but also many newspapers that had circulations of fewer than 5000 and served small, impoverished communities.
The big picture reveals that, in an era of misinformation, social media and news aggregators, news media companies are under pressure, and journalism jobs are being cut. There is some hope in the shape of new players entering the market and hiring journalists, including in the shape of digital natives such as Vice and Buzzfeed. However, in 2019 these two companies were among the many that announced significant staff layoffs (Goggin 2019) . What's more, as Australia's ACCC notes, these publications 'tend to employ relatively few journalists' (ACCC 2019). Even accounting for new arrivals, the number of journalism jobs in Australia is falling (see Jobs Data Analysis and Results), and as a result there are areas (including local government, local court, health and science issues) that journalism is no longer covering adequately (ACCC 2019).
Further research is also revealing a clearer profile of the typical journalist, and also the typical journalist who loses his/her job. Drawing on 2017 data, one study found that journalism jobs internationally are largely filled by a young, inexperienced and itinerant workforce (Josephi and Oller Alonso 2018) . Meanwhile, research suggests that it is journalists with extensive experience who are losing their jobs (at least in Australia) . And those who lose their jobs face decidedly uncertain futures. In longitudinal research tracking the post-journalism careers of Australian journalists who had been made redundant, many of those surveyed revealed they were experiencing job precarity. Further, a significant minority had moved into strategic communications or public relations (Zion et al. 2018) .
The impacts of COVID-19. The advertising crisis for journalism has been described not as a single black swan, but as a flock of black swans (Doctor 2020) . According to one estimate, from 2006 to 2020, US newspapers lost more than 70 percent of their ad dollars (Doctor 2020) . And then came COVID-19. Just as the coronavirus has been claiming lives, it has also been claiming journalism jobs, with particularly devastating impacts on regional and local news outlets. This is true in many countries, including the US. In March, layoffs were announced at the Detroit Metro Times and its six sibling mastheads, with remaining staff told their pay would be cut (Flynn 2020) . With concerts cancelled and restaurants shuttered, promoters and restaurateurs had nothing to advertise. On March 25, 2020, The Atlantic ran a story under the headline, 'The coronavirus is killing local news' (Waldman and Sennott 2020) . The story called for government and philanthropic intervention, and for people to subscribe: 'Among the important steps you should take during this crisis: Wash your hands. Don't touch your face. And buy a subscription to your local newspaper.' In a matter of weeks, many American news websites' advertising revenues are said to have fallen by as much as 50%. As one media expert noted in late March, 'Advertising, which has been doing a slow disappearing act since 2008, has been cut in half in the space of two weeks' (Doctor 2020) . Flynn (2020) reported in March, 'At least 100 people have lost their jobs in media over the past two weeks, with most outlets citing coronavirus as the direct cause.'
In the UK in April, The Guardian reported that newspapers were set to lose 57million if the outbreak lasted for another three months (Sweney 2020) . This was partly because advertisers were refusing to place their ads next to stories about the pandemic, which they deemed to be inappropriate content.
In Australia too, as we have seen, there were widespread closures and job losses before coronavirus, but COVID-19 compounded the problem. In late March, Rupert Murdoch's publishing business News Corp warned of 'inevitable' job cuts and the closure of regional titles (Meade 2020b) . Soon afterwards, News Corp Australia's biggest publishersuspended the print editions of 60 Australian newspapers, including the Manly Daily and Wentworth Courier in Sydney, the Brisbane News and the Mornington Peninsula Leader in Victoria (Meade 2020b) . The cuts came in the wake of a dramatic drop in advertising from the entertainment, restaurant and real industries, the titles' main revenue sources.
In many countries, governments have announced assistance packages. On April 6, the Australian government announced it would bring forward the release of $5million from its Regional and Small Publishers Innovation Fund to support public interest journalism during COVID-19 (Fletcher 2020) . In April 2020, the Danish government allocated approximately 24m to save local media. 'The scheme can compensate for the lost advertising revenue,' said culture minister Joy Mogensen (Zalan 2020) .
By contrast, however, some governments are making the coverage of coronavirus harder. In China, authorities have cracked down on doctors and reporters who exposed the outbreak (Kuo 2020) ; in the US, journalists are being barred from talking to staff at public hospitals (Carville et al. 2020) ; and in countries including Venezuela, Niger and India, journalists have been arrested and intimidated (CPJ 2020) .
Job ads as a proxy for labour demand. Job ads provide 'leading' indicators of shifting labour demands as they occur, as opposed to the 'lagging' indicators from labour market surveys. Consequently, job ads are increasingly used as a data source for analysing labour market dynamics (Markow et al. 2017; Blake 2019) . For instance, job ads data have also been used to assess labour shortages. Dawson et al. (2019) defined a range of indicators to evaluate the presence and extent of shortages, such as posting frequency, salary levels, educational requirements, and experience demands. They also built a metric based on the forecasting error from Machine Learning models trained to predict posting frequency. Intuitively, occupations experiencing high posting volatility are difficult to predict. Subsequent work showed these indicators to be predictive of labour shortages in the Australian Labour Market . In the present research, in Jobs Data Analysis and Results, we use a similar set of indicators to analyse labour demand for journalists. Further details on job ads data are provided in the Supplemental Material.
Analysing journalism jobs with job ads. Journalism jobs have also previously been analysed using job ads. Young and Carson (2018) collected and assessed how Australian media outlets defined journalism job positions when hiring journalists from November 2009 to November 2010. The authors used a content analysis methodology and manually labelled data fields, such as employer, educational qualifications, job responsibilities, experience requirements, location, work hours, media platform, skill demands, job title, and any other miscellaneous information. The authors found that journalism was not a high priority during this period; instead employers advertised four times as many job ads for sales, marketing, and advertising positions.
More recently, Guo and Volz (2019) conducted content analysis on 669 journalist job announcements from US media organisations, as posted on Indeed.com from 1 July to 31 December 2017. The authors' objective was to define, compare, and analyse the journalists' expertise requirements as expressed through job ads. To achieve this objective, the authors manually reviewed and codified job vacancies. This research found that 'multi-skilled' journalists are experiencing higher levels of demand. The authors also found that journalists' ability to flexibly adapt to changing situations was a characteristic of growing importance. These studies, while significant, are relatively limited in scope. In this paper, we analyse a nine-year long dataset which allows us to uncover longitudinal dynamics of journalism jobs.
Limitations of job ads data. Job ads data are an incomplete representation of labour demand. Some employers use traditional forms of advertising for vacancies, such as newspaper classifieds, their own hiring platforms, or recruitment agency procurement. Furthermore, anecdotal evidence reveals that some vacancies are filled informally, using channels such as word of mouth, professional networks and social media. Job ads data also overrepresent occupations with higher-skill requirements and higher wages, colloquially referred to as 'white collar' jobs (Carnevale et al. 2014 ). Finally, just because a job is advertised, does not mean that the position will be, or has been, filled.
Employment statistics and occupational standards. Employment statistics provide data on populations employed in standardised occupational classes. Occupations in Australia correspond to their respective occupational classes according to the Australian and New Zealand Standard Classification of Occupations (ANZSCO) (Australian Bureau of Statistics 2013).
There are significant shortcomings to analysing occupations within ANZSCO categories. Official occupational taxonomies (like ANZSCO) are often static and are rarely updated, therefore failing to capture emerging skills, which can misrepresent the true labour dynamics of particular jobs. For example, the occupational class of 'Print Journalist' has been a constant in Australian occupational statistics. Yet, the underlying skills of a 'Print Journalist' have changed dramatically in recent decades.
To overcome the above-stated limitations, in our data construction, we leverage the BGT occupational ontology together with the ANZSCO ontology. We also use the rich skill-level information from job ads that are missing from occupational employment statistics to build an encompassing journalism job ads dataset.
This research uses both labour demand and labour supply data to analyse journalism jobs. On the labour demand side, we use a detailed dataset of over 6.7 million Australian job ads, spanning from January 2012 to March 2020. These data were generously provided by Burning Glass Technologies * (BGT). For labour supply data, we leverage official employment statistics (Australian Bureau of Statistics 2019a) and salary levels (Australian Bureau of Statistics 2019b) provided by the Australian Bureau of Statistics (ABS) over the same period. These data sources provide longitudinal employment and salary information that have been disaggregated by gender, location, and types of employment (full-time and part-time). Further details of data sources and data construction are provided in the Supplemental Material.
To analyse the underlying journalism skills within occupations, we implement a skill similarity methodology adapted from Alabdulkareem et al. (2018) and then by Dawson et al. (2019) to calculate the pairwise similarities between skills from job ads.
Skill similarity. Two skills are similar when the two are related and complementary, i.e. the two skills in a skills-pair support each other. For example, 'Journalism' and 'Editing' have a high pairwise similarity score because together they enable higher productivity for a journalist;
whereas 'Journalism' and 'Oncology' have a low similarity because they are generally seldom used jointly. We measure the similarity of skill-pairs based on their co-occurrence patterns in job ads, while accounting for skill ubiquity and specialisation. To capture how journalism skills have changed over time, we measure skill similarity during calendar years.
Formally, given J as the set of job ads posted during a specific calendar year, we measure the similarity between two skills s and s as:
where j and j are individuals jobs ads from the set J, and e(s, j) ∈ {0, 1} measures the importance of skills s for job j using theory from Trade Economics (Hidalgo et al. 2007 ). Skills s and s are considered as highly complementary if they commonly co-occur and are both 'important' for the same job ads. Finally, θ(s, s ) ∈ [0, 1], a larger value indicates that s and s are more similar, and it reaches the maximum value when s and s always co-occur (i.e. they never appear separately).
We build the top yearly lists of journalism skills by computing θ(Journalism, s) -i.e. the similarity between the skill 'Journalism' and each unique skill that occurs for each year from 2014-2018. The yearly top 50 most similar skills to 'Journalism' are shown in the Supplemental Material together with the full details of the θ measure.
Journalism skill intensity. Finally, we determine the occupations that most require the top journalism skills uncovered from the above. We propose η, the 'Journalism Skill Intensity', for each standardised BGT occupation, defined as percentage of journalism skills relative to the total skill count for the job ads related to an occupation o. Formally:
where D is the set of journalism skills, and O is the set of job ads associated with the occupation o. This method allows us to adaptively select occupations based on their journalism skill intensity.
In this section, we perform a data-driven analysis of journalism jobs in Australia based on job ads data and official occupational statistics. First, we longitudinally examine key features of jobs data, such as employment levels, job ads posting frequency, salaries, and posting frequency growth and predictability level. We also analyse how the underlying skills of journalists have changed over time, and which skills and occupations are growing in similarity to journalism. 
In Australian journalism, 2012 is considered a watershed
year. An estimated 1,500 journalists were made redundant, the majority of those from Australia's two largest print companies, Fairfax Media (now Nine Entertainment) and News Limited (now News Corp Australia) (Zion et al. 2016) . The severity of this industrial shock can be observed in Fig. 1 . Against the left y-axis, the blue line shows quarterly job ads posting frequency for journalism jobs. As the graph depicts, posting frequency for journalism job ads experienced extremely low levels in 2012 until 2013, when they began to increase. The volume of vacancies increased until mid-2014, before plummeting in late-2014 to the levels last seen in 2012. From 2015, journalism job ads experienced strong growth, reaching a peak in mid-2016. Since then, journalism job ads have trended downward until the end of 2019, albeit with volatile peaks and troughs. In summary, the data shows that journalism job ads have not been in freefall since 2012. Rather, there was erratic growth in journalism job ads until a peak in 2016, followed by erratic decline. Similarly, employment levels underwent immense volatility from 2012 to 2013. Against the right y-axis of Fig. 1 , the orange line shows the number of quarterly employed for 'Journalists & Other Writers' at the ANZSCO Unit level. Employment levels peaked in mid 2012, before dramatically dropping in early 2013. This is an effect of the the mass journalist redundancies made in 2012, given that employment statistics are 'lagging indicators' and it takes time for labour markets to reflect changes in occupational statistics. Early 2013 marked the lowest point of journalist employment seen in this time-series. As also observed in job ads data, journalist employment levels grew until 2016-2017 and has since trended downwards, exhibiting volatile quarterly changes through to the end of 2019.
COVID-19 and journalism jobs. The early effects of COVID-19 are apparent in the posting frequency of job ads in Australia. This is the case for most occupations, including journalists. At the time of writing, official Australian employment statistics were not yet available, making it difficult to determine the extent of job losses caused by the pandemic. However, job ads provide a leading indicator of labour demand (Dawson et al. 2019 ). Higher vacancy rates typically mean higher levels of labour demand by employers, which is a critical component of healthy labour markets. As Fig. 2 highlights, vacancy volumes have declined for both journalism jobs and at aggregate levels in Australia. Since mid-February, weekly posting frequency has decreased across all Australia job ads, as seen in Fig. 2a . Such a decline this early in the year is atypical. As show, the frequency of job ad postings follow a yearly seasonal pattern, with late February and early March typically being a period of upward trend growth. However, late February and early March 2020 coincided with the International outbreak of COVID-19. During this period, the Australian government instituted widespread quarantine and social distancing measures, which significantly constrained economic activity (Boseley and Knaus 2020) . The impacts of these COVID-19 containment laws are starkly apparent in Fig. 2b . Posting frequency for journalism jobs are down 63% when comparing March 2019 volumes to March 2020. This is significantly higher than the aggregate market of all Australian job ads, which is down 37% over the same period. Fig. 2b shows that Melbourne appears to be the city hardest hit, recording no journalism job ads in March 2020 and only 3 posts for the first quarter of 2020. Clearly the pandemic is having a highly damaging effect on the journalism jobs market.
We compare salaries extracted from job ads with ABS reported wage data for 'Journalists and Other Writers' † . Fig. 3 reveals two main findings regarding journalist salaries. First, according to job ads data, journalists attract considerably lower annual wage levels (solid blue line) than the market average (dashed blue line). As of 2018, job ads indicate that journalists earn approximately $10,000 less than the market average. These findings, however, are somewhat contrary to the wage earnings data collected by the ABS (Australian Bureau of Statistics 2019b), according to which 'Journalists and Other Writers' (solid orange line) have been earning a growing wage premium over the market average (dashed orange line) since 2014. This discrepancy can be explained by the fact that job ads data tend to overrepresent occupations in the 'Professional' and 'Manager' classes (Carnevale et al. 2014) , which typically attract higher wages. As a result, the average salary levels from job ads data (dashed blue line) are about $20,000 higher than average salary levels from ABS data (dashed orange line), from 2014 to 2018. However, the salary levels for journalists are very similar when comparing across the two data sources. Fig. 3 yields a second observation: journalist salary levels increased in both absolute and relative terms compared to average market levels, between 2012 to 2018 in both data sources. More importantly, the relative salary growth of journalists has exceeded the market averages, during the period studied. * BGT is a leading vendor of online job ads data.
https://www.burning-glass.com/ † ABS wage data is reported biennially, with the latest reporting year being 2018. Therefore, wage values in the 'odd' years in between the reporting periods were interpolated, calculated as the mean of the previous and the subsequent years. 
Posting trends. We constructed an auto-regressive Machine Learning model to predict posting frequency of journalism job ads in Australia (Dawson et al. 2019 Quantify labour demand volatility. When constructing Machine Learning models, it is standard procedure to use error metrics to evaluate the prediction accuracy. Volatility in posting volumes inherently lead to lowered prediction performance. Here we use the prediction error measured using the 'Symmetric Mean Absolute Percentage Error' (Scott Armstrong 1985; Makridakis 1993 ) as a proxy for the the volatility of labour demand for different occupations (see the technical section in the Supplemental Material for more details). for the volume of 'All Australian job postings'. We use a sliding window approach to obtain multiple predictions (see the Supplemental Material) that we aggregate as boxplots.
The higher the error score on the vertical axis, the lower the predictive abilities for that occupation. As Fig. 5 reveals, predicting the daily posting frequency of journalism jobs is consistently more difficult than for the other occupations, and the market as whole. 'Data Scientists', an occupation undergoing strong relative growth, is also showing a high prediction error compared to the market as a whole, indicative of experiencing a degree of volatility. However, it is not nearly commensurate to the predictive difficulties, and volatility, of journalists. This was true from 2012 to 2019, and has become worse in 2020 with the spread of COVID-19.
There have been growing gender differences of employed journalists in Australia since 2014. Fig. 6a shows that the ratio of female employed journalists has increased relative to male journalists (ANZSCO Unit Level) (Australian Bureau of Statistics 2019a). In 2014, the female-to-male employment ratio was 0.7. In 2018, the proportion more than doubled, with almost 1.8 female journalists employed for every male journalist. It has since declined in 2019 to 1.35, but this proportion is still almost double that of 2014. Fig. 6b also shows that wage inequality between female and male journalists has worsened (Australian Bureau of Statistics 2019b). Since 2014, the annual salaries for female journalists increased by only AU$3,000, whereas annual salaries for male journalists increased by more than AU$30,000. Male journalists thus experienced an average wage growth that was ten times greater than female journalists from 2014 to 2018.
There are also changing age demographics of employed journalists during the studied period. The markers on Fig. 6b highlight the average age of journalists by gender, per year. Male journalists have been getting older, their average age increasing by two years from 2014 to 2018. Female journalists, however, have been steadily getting younger. The average age for female journalists decreased by more than four years from 2014 to 2018. Fig. 7 plots the location and volume of employed journalists in Australia. Fig. 7a shows the absolute and relative number of job ads posted for each of the capital cities, and outside them, and Fig. 7b shows the location of employed journalists per state. Unsurprisingly, Sydney and Melbourne, the respective capital cities of New South Wales (NSW) and Victoria (VIC), consistently have the highest job ad posting frequencies. However, the relative share of job ad posting frequency in Australian capital cities has shrunk in recent years, with Fig. 7a showing an increase outside of major cities, both in relative and absolute terms. This trend reached a peak in 2017, when less than 50% of all journalist job ads were for positions inside capital cities. A small rebound followed, and in 2019 Sydney commanded approximately one-third of all journalism job ads.
Figs. 8a and 8b show respectively the number of years of formal education required for journalists, and the experience requirements (both per year, extracted from job ads data) The education requirements consistently remained at market average levels, with journalists required to possess a Bachelor-level degree (approximately 16 years of education).
By contrast, the experience requirements have been more variable. Since 2012, employers have required fewer years of experience from journalists than is required in the market generally. However, the gap is narrowing. In 2018, employers demanded of journalists, on average, one additional year of experience compared to 2014. This counters the general market trend of employers demanding less experience of prospective employees.
Casual and temporary work have become more commonplace in Australia (Gilfillan 2018) , and we study if this is also the case for Australian journalism jobs. In Fig. 9 we plot the number of permanent and temporary journalism jobs, per calendar year. The number of 'Temporary' journalism jobs has increased in absolute terms since 2012, and they have made up the majority of all journalism ads in every year. It is noteworthy too that the share of 'Permanent' journalism vacancies has also increased since 2012. However, this trend should be interpreted with a degree of scepticism as only ∼ 50% of all journalism job ads specify whether the roles advertised are permanent or temporary.
Growing demand for journalism skills. Here we perform a detailed analysis of the top 50 journalism skills that we identify for each year from 2014 to 2018 (see Data & Methods for details, and the Supplemental Material for the top 50 skills for each year). We calculate (and show as stacked bar charts in Fig. 10a ) the posting frequency of three of the fundamental journalism skills within job ads: (1) 'Journalism', (2) 'Editing', and (3) 'Writing'. These skills are counted across all job ads in Australia, regardless of their occupational class. While Fig. 4 shows that labour demand for journalists has decreased since 2016, Fig. 10a presents the more nuanced story that the posting frequency for each of these core journalism skills has increased every year from 2012 to 2018. The relative rankings of these three skills have also increased. For each year, we count the posting frequency of each unique skill that appears in job ads. We then rank these skills by posting frequency as a proxy for labour demand. Fig. 10b shows that the rankings of all three of these fundamental journalism skills have improved from 2012 to 2018. In other words, not only has the posting frequency of these three journalism skills increased in job ads, but their importance relative to all other skills has also increased.
Changing importance of journalism skills. Here, we aim to determine whether a change occurred in the relative importance of the core journalism skills over time. Given the dynamics of skill requirements in job ads, skills can become increasingly more (or less) similar over time. We use the similarity measures in Eq. (1) to identify the skills that are becoming more relevant to being a journalist. Fig. 11a shows the changes in similarity scores between the skill 'Journalism' and each of the eight other top journalism skills (as per the top yearly journalism skills lists). The greater the area covered in the radar chart, the greater the similarity score, with the blue area representing 2014 and the red area 2018. Visibly in Fig. 11a , 'Social Media' related skills are becoming increasingly relevant for journalists, with the relative ratio of more traditional skills such as 'Editing' and 'Copy Writing' diminishing with respect to 'Social Media', from 2014 to 2018.
Occupations that require journalism skills. Here we study which are the occupations that require most journalism skills, and their dynamics over time. Given the yearly lists of top journalism skills (described in Skill Similarity), we use Eq. (2) to determine the occupations with the highest intensities of journalism skills, for each year from 2014 to 2018. Intuitively, this allows us adaptively to identify occupations that become more or less similar to 'Journalism', based on their underlying skill usage. It also provides a means to assess likely transitions between occupations, as workers are more likely to transition to occupations where the underlying skill requirements are similar (Bechichii et al. 2018) . Higher similarity lowers the barriers to entry from one occupation to another. high in 2018, their growth since 2014 was relatively low. In comparison, 'Photography', 'Communications', 'Social Media', and 'Public Relations' experienced higher journalism skill intensity growth from 2014 to 2018. This provides evidence as to where workers with journalism skills might be finding employment outside of journalism.
Drawn from job ads and employment statistics, our findings reveal the highly volatile nature of the journalism industry. Compared to other industries, journalism experiences dramatic fluctuations that are unpredictable and irregular. The data also confirms that journalism is an industry in crisis, particularly since the spread of COVID-19 (see below). However, the data also reveals surprises, including that the number of journalism jobs ads and employment levels increased from 2012 until 2016. Since then, though, journalism jobs in Australia have been in decline. The volatility of journalism jobs in Australia is clearly apparent in Posting Frequency & Employment levels. Posting frequency of job ads have ranged from near zero levels in 2012 and 2014 to more than 200 posts per quarter in 2016. These violent swings are also apparent in the quarterly employment statistics of 'Journalists and Other Writers'. Following the mass redundancies of 2012, employment levels plummeted, reaching their lowest levels in 2013. They have since increased. However, the data confirms that volatility of employment has been a constant for journalism, and that this has worsened during COVID-19. Fig. 5 reveals this extreme volatility. The error metrics from the Machine Learning model used to predict daily posting frequencies of job ads (as detailed in Trend Analysis & Predictability) highlight the difficulties of making predictions about journalism employment. This lack of predictability is indicative of volatility. The higher the error scores for a given occupation, the higher the likelihood that the occupation is experiencing significant disruption. This becomes apparent when we compare journalism to other occupations. For example, the volatility of 'Journalists' dwarfs that of 'Data Scientists', an occupation experiencing significant demand and volatility in Australia (Dawson et al. 2019) .
The volatility of journalism jobs is further revealed by a time series analysis of journalism compared to other occupations (Fig. 4) , a gender-based analysis (Fig. 6) , a geographical analysis (Fig. 7) and an analysis of the temporary nature of journalism jobs (Fig. 9) . What is indisputably clear is that the advertising market for news and journalism has collapsed, and continues to collapse. Meanwhile, consumers have consistently shown an unwillingness to pay for digital journalistic content. In 2019, Australian news consumers admitted they would much would rather subscribe to a video streaming service such as Netflix (34%), than pay for online news (9%) (DNR Australia 2019). The Internet has detonated the advertising model that once sustained journalism, and simultaneously re-adjusted consumer expectations on the monetary value of journalism content. The fact that journalism is struggling is confirmed in several ways by the data, including by the unpredictability of job ads posting frequency and the clear shifts in employment levels, as shown in Fig. 1 . To say that journalism is being disrupted is an understatement.
Volatility exacerbated by COVID-19. In a fragmenting news ecosystem, consumer demand for news and journalism is difficult to quantify. The Digital News Report: Australia 2019 has found that many consumers are disengaging, with the proportion of Australians avoiding news increasing from 57% in 2017 to 62% in 2019 (Fisher et al. 2019) . Demand for 'quality' and 'public interest' journalism is even harder to quantify, given ongoing debates as to what exactly constitutes 'quality' and 'public interest' (Wilding et al. 2018) . Nonetheless, demand for journalism has surged dramatically since the outbreak of COVID-19. The irony of the coronavirus pandemic is that even as it has been killing off journalism jobs, it has also created a heightened demand for, and appreciation of, journalism among the general public. As news analyst Doctor (2020) wrote of the US situation in late March, 'The amount of time Americans spend with journalists work and their willingness to pay for it have both spiked, higher than at any point since Election 2016, maybe before ... [but] how many journalists will still have jobs once the initial virus panic subsides?'. In the UK in March, The Guardian received 2.17 billion page views, an increase of more than 750 million above its previous record, set in October 2019 (Bedingfield 2020) .
Since the outbreak of COVID-19, the volatility of the journalism jobs market has worsened dramatically. We noted above that in early April News Corp suspended the publication of 60 newspapers nationally. Then, on April 14, Australian Community Newspapers, which publishes 170 community titles, said it was suspending publication of some of its non-daily newspapers; as a result, four printing presses were closed and an unspecified number of staff were stood down (Meade 2020a ). The following day, the federal government announced a $50million package to support public interest journalism across TV, newspapers and radio in regional and remote Australia (Hayes and Rubbo 2020) . And on April 20, the government announced that digital platforms including Google and Facebook would be forced to pay for content as the internet advertising business would be overhauled to help local publishers survive the economic fallout of the coronavirus crisis (Crowe 2020) . The scheme, which would involve a mandatory code imposed on digital giants, would potentially set a global precedent. The combined and ongoing impact on journalism jobs of these sudden, cumulative developments are hard to predict, but will no doubt be profound.
At first glance, the data seems to suggest that gender equity is finally arriving in Australia for journalism -an industry that has traditionally been male-dominated -as more women than men are employed. As the data shows, in 2014 there were 0.7 female journalists employed for every male Journalist, but by 2018 the proportion of female-to-male employment more than doubled, with almost 1.8 female journalists employed for every male Journalist. It then declined in 2019 to 1.35, a proportion still almost double that of 2014.
However, further detail reveals that equity remains elusive. Specifically, wage inequality has worsened. Since 2014, annual salaries for female journalists increased by AU$3,000, compared with an increase for male journalists of over AU$30,000 over the same period. From 2014 to 2018, average wage growth for Male journalists was more than ten times greater than for female journalists. Meanwhile, the average male Journalist has been getting older, while the average female Journalist has been getting younger. In 2014, the average age for a Journalist, whether male or female, was roughly the same: late 30s. By 2018, the average age for a male journalist was 42, whereas for a female journalist it was 34.
The potential impacts of this worsening disparity are concerning. It is likely that senior positions responsible for major editorial decisions are increasingly being dominated by men, whereas junior roles are being filled by women who are younger and worse-paid. This may be having a flow-on effect as to which news stories are being covered, and how those stories are being covered. In other words, the gender gap and age gap may be having an impact on the content of the news. Further research is needed into related issues of the industrys composition, including, for instance, the ethnicity of journalists. A vast body of literature exists regarding the importance of diversity in news (Rodrigues and Paradies 2018; Budarick and Han 2017) . Further work is needed into diversity (and its various sub-categories), and what effect diversity has, for instance, on the proportion of people who are actively avoiding the news.
As discussed above, the sustained pressures on regional and local journalism have led to a worrying growth of news deserts in countries including Australia and the US. This trend has been accelerating alarmingly since the outbreak of COVID-19, leaving many areas without any regional or local news coverage. Hence we might assume that journalism jobs in regional and local areas have been drying up, and that an ever-increasing proportion of journalism jobs are in urban centres.
The data, however, is not so clear. As Fig. 7a shows, in 2012 fewer than a quarter of Australias journalism job ads were for jobs outside Sydney, Melbourne, Brisbane, Canberra and the ACT or Perth. In every subsequent year, the proportion of job ads for journalism positions outside these urban centres has been considerably higher. The peak came in 2017, when nearly half of all job ads were for positions outside the major cities. Does this suggest that in 2017 there were as many jobs for journalists in the regions as in the centres? Surely not. The explanation, we would suggest, lies in various factors. These include that regional journalism jobs are hard to fill, perhaps because they offer relatively low salaries, and are hence re-advertised. It is also possible that there is a high turnover for some regional positions. In short, the job ads data may simply be an indication that the journalism industry is even more volatile in the regions than in major urban centres.
Research consistently and emphatically reveals that regional and local journalism are suffering, with an increasingly bleak prognosis of cuts and closures. While the data shows a surprisingly high proportion of journalism job ads for positions outside the main metropolitan centres, this cannot be taken to suggest that journalism is holding steady in these areas.
Skills are the building blocks of jobs and standardised occupations. In this regard, occupations can be characterised as 'sets of skills'. Intuitively, skills that are similar can be interpreted as complementary when they are paired together or relatively easy to acquire (in either direction) when one skill is already possessed.
This intuition provides insight into how journalism skills are evolving and where journalists might be finding alternate career paths. As Fig. 1 shows, both the demand for and supply of journalists have been declining in Australia since 2016. Therefore, a growing number of former journalists, who presumably possess an assortment of journalism skills, have needed to transition between occupations to find new work. There are, however, significant transition costs moving between jobs (Bechichii et al. 2018; Bessen 2015) . These costs can come in the form of education, training, physically moving for new employment and other barriers. To reduce the friction of these transition costs, workers tend to leverage their extant skills, in concert with acquiring new skills, to make career transitions.
As seen in Fig. 11a , the skill 'Journalism' has become more similar to 'Social Media' and more 'generalist' communications skills. After applying the Skill Intensity formula from Eq. (2), we identified the top occupations with highest intensities of journalism skills from 2014-2018. The Fig. 11b chart reinforces that top journalism skills are becoming more important to other occupations, such as 'Photographers', 'Social Media Strategists', 'Public Relations Professionals', and 'Communications Specialists'.
From the data, we suggest, three conclusions can be drawn. First, to be hired, journalists are required to have a wider array of skills, such as photography and social media aptitude. Second, jobs in journalism are increasingly jobs in social media, generalist communications, and public relations rather than in reporting and editing. And third, we see hints as to where onetime journalists are finding alternate career paths. As employment conditions progressively worsen, journalists are seemingly pursuing new careers in the occupational areas seen in Fig. 11b , such as photography or public relations.
At a time of great uncertainty, with employment prospects deteriorating, it is no wonder that journalists look beyond traditional journalism for their futures. For society, however, the implications are significant. In this time of economic uncertainty and polarising politics, the people who possess the journalism skills required to keep the public informed and hold leaders to account are, in many cases, employing their talents elsewhere. This places enormous strain on the health and quality of journalism in Australia.
The data reveals a contradiction: demand for journalism skills has increased at the same time that demand and employment for journalists has declined. Indeed, this is one of several contradictions in a volatile industry. For an increasing number of news media organisations, a sustainable business model remains elusive.
Our findings give a clearer outline of the problem. Unfortunately, the solutions remain less clear. Quality journalism is expensive. Good reporting is often slow and laborious, fixed to the unfolding story. What is required of quality journalism is, therefore, at odds with the prevailing employment conditions. This paper highlights the stresses experienced by journalism in Australia by analysing jobs data. We observe the volatility and downward trajectory of the occupation both in job ads and employment statistics. These unfavourable employment conditions are being worsened by the unfolding COVID-19 crisis. Our longitudinal analysis also yields important findings regarding gender inequity. While women are representing a greater share of employed journalists, they are earning less, and the wage gap is growing.
Further, this paper has also identified top journalism skills. Adopting a data-driven method, we described which skills are most similar to 'Journalism'. We then used these yearly skill sets to adaptively similar occupations. This enabled us to quantitatively show that the skill demands of journalists are becoming similar to those of 'Social Media Strategists', 'Public Relations Professionals', 'Communications Specialists', and others. This suggests where people with journalism skills are likely finding alternate career paths, but also raises a related concern. On the face of it, the journalism jobs data we have analysed does not look so bad after all. On reflection, however, it suggests that the thinning ranks of 'journalism' are populated by fewer journalists, and more public relations specialists.
Future research could compare these results to other labour markets to assess the validity of these findings. For example, the skill similarity methodology could be applied in other labour markets to compare the resulting top journalism skills in different locations. Additionally, labour demand analyses could be conducted on occupations most similar to journalists to better understand the incentives to transition to other vocations.
The results from this research both reinforce the welldocumented difficulties of journalism in Australia and provide granular details that isolate and reveal these challenges. The implications are global. The hope is that these analytical methods and insights can contribute to the health and well-being of the Fourth Estate, and hence to the health and well-being of society. 
Here, we describe the data sources we used to analyse journalism jobs. We also outline the skill similarity methodology that enables us to construct temporal (yearly) sets of top journalism skills. Lastly, we describe how these temporal sets of top journalism skills then allow us to adaptively identify occupations that are 'most similar' to journalism, at the granular skill level.
Journalism job ads. This research draws on more than 6.7 million Australian online job ads from 2012-01-01 until 2019-02-28, courtesy of data provided by Burning Glass Technologies ‡ (BGT). BGT also granted access to the aggregated job ads data from 2019-03-01 to 2020-03-31, allowing us to address the early impacts of the unfolding coronavirus pandemic (COVID-19) on journalism jobs in Australia. BGT collected the job ads data via web scraping and systematically processed it into structured formats. The dataset consists of detailed information on individual job ads, such as location, salary, employer, educational requirements, experience demands, and more. The skill requirements have also been extracted (totalling > 11, 000 unique skills) and each job ad is classified into its relevant occupational and industry classes. There are two occupational ontologies in the job ads dataset. The first is ANZSCO, which is the official occupational classification standard in Australia and New Zealand. The other is the BGT occupational ontology, which has been developed due to shortcomings of official occupational standards (as described in Related Work & Background).
To ensure selection accuracy, we instituted the following search query conditions over the dataset:
1. All job ads with ANZSCO Occupation labels of 'Newspaper or Periodical Editor', 'Print Journalist', 'Radio Journalist', 'Television Journalist', and 'Journalists and Other Writers nec' (where 'nec' stands for 'not elsewhere classified').
2. OR All job ads with the BGT Occupation label of 'Journalist / Reporter' and 'Editor' (the two primary BGT occupational classes for journalists);
3. OR All job ads with the 'Journalist', 'News', or 'Editor' in any part of the job title.
After manually reviewing the returned job ad features for accuracy, the selection process resulted in a sample of 3,231 Australian journalism job ads from 2012-01-01 until 2019-02-28. We used the same search query and approach for the 2019-03-01 to 2020-03-31 period to supplement this sample. This returned 467 journalism job ads, amounting to a total of 3,698 journalism job ads from 2012-01-01 to 2020-03-31. The job ads during the period are observed aggregated daily, with limited skill level details. However, much of the analysis that follows requires access to the features within individual job ads, so only Fig. 2 leverages the 2020 data.
Further details on job ads data. It is estimated that approximately 60% of Australian job ads are posted online (Department of Employment, Skills, Small and Family Business 2019). At aggregate levels, online job advertisements (ads) provide valuable indicators of relative labour demands. This includes demand features, such as salaries, educational requirements, years of experience, and, most importantly, skill-level information. Here, a distinction must be made between skills, knowledge, abilities, and occupations. 'Skills' are the proficiencies developed through training and/or experience (OECD 2019); 'knowledge' is the theoretical and/or practical understanding of an area; 'ability' is the competency to achieve a task (Gardiner et al. 2018) ; and 'occupations' are standardised jobs that are the amalgamation of skills, knowledge, and abilities used by an individual to perform a set of tasks that are required by their vocation. Throughout this paper, the term 'skill' will incorporate 'knowledge' and 'ability'. Skills, in this sense, are the constituent elements that workers use to perform tasks, which ultimately define jobs and occupations.
Advantages of job ads data. Understanding how the composition of skill sets evolve within an occupation is essential to understanding trends in that occupation. However, occupational data rarely captures skill-level data. Most often, official occupational standards are static, rarely updated classifications, which fail to capture the changing skill demands of occupations, or to detect the creation of new types of jobs.
Journalist employment statistics. Employment data (labour supply) were collected from the 'Quarterly Detailed Labour Force' statistics by the ABS (Australian Bureau of Statistics 2019a). These employment data are organised into standardised occupations called the Australia and New Zealand Standard Classification of Occupations (ANZSCO). ANZSCO provides a basis for the standardised collection, analysis and dissemination of occupational data for Australia and New Zealand. The structure of ANZSCO has five hierarchical levels -major group, sub-major group, minor group, unit group and occupation. The categories at the most detailed level of the classification are termed 'occupations'.
A shortcoming, however, is that the lowest level of occupational employment data available by the ABS is at the 4-digit Unit level, which is one hierarchical level above specific occupations. As our research is focused ‡ BGT is a leading vendor of online job ads data.
https://www.burning-glass.com/ on the employment Unit class of 'Journalists and Other Writers', all ABS employment statistics cited in this research include the following occupations: 'Copywriter', 'Newspaper or Periodical Editor', 'Print Journalist', 'Radio Journalist', 'Technical Writer', 'Television Journalist', and 'Journalists and Other Writers nec' . While the inclusion of the 'Copywriter' and 'Technical Writer' occupations in these statistics could distort results pertaining to 'Journalists' to an extent, we consider this impact to be limited in scope. As we describe in Jobs Data Analysis and Results, the employment statistics highlight important trends in journalism occupations, which are confirmed by findings from the job ads data.
Another shortcoming of employment statistics is their 'lagging' nature. The inertia of labour markets means that it takes time for changes to materialise in employment statistics. Additionally, the official reporting of employment statistics takes time. Employment statistics are often published several months or years after the reported period. As a result, these 'lagging' characteristics are not available for the most recent periods in our work (such as for the second half of 2019 and later.)
In this section, we detail the methodology previously employed in (Alabdulkareem et al. 2018; Dawson et al. 2019) to dynamically measure skill similarity. Here, we present the building blocks for this method, applying it for journalism related skills and occupations.
Intuition. Two skills are similar when the two are related and complementary, i.e. the two skills in a skills-pair support each other. For example, 'Journalism' and 'Editing' have a high pairwise similarity score because together they enable higher productivity for the worker, and because the difficulty to acquire either skill when one is already possessed by a worker is relatively low.
Our goal, therefore, is to calculate the similarity of each unique skill relative to every other unique skill in the dataset. Such a measure allows us to identify which skills have the highest pairwise similarities to a specific skill or set of skills. We also want to identify how skill similarity evolves over time. To achieve this, we have instituted a temporal split of a calendar year. This enables us to assess yearly changes to the underlying skill demands of journalism jobs.
The Revealed Comparative Advantage of a skill. We implement a data-driven methodology to measure the pairwise similarity between pairs of skills that cooccur in job ads. One difficulty we encounter is that some skills are ubiquitous, occurring across many job ads and occupations. We address this issue by using the Revealed Comparative Advantage (RCA), which maximises the amount of skill-level information obtained from each job ad, while minimising the biases introduced by overexpressed skills in job ads. Formally, RCA measures the relevance of a skill s for a particular job ad j as:
where x(j, s) = 1 when the skill s is required for job j, and x(j, s) = 0 otherwise; S is the set of all distinct skills, and J is the set of all job ads in our dataset. RCA(j, s) ∈ 0, j ∈J,s ∈S
x(j , s ) , ∀j, s, and the higher RCA(j, s) the higher is the comparative advantage that s is considered to have for j. Visibly, RCA(j, s) decreases when the skill s is more ubiquitous (i.e. when j ∈J
x(j , s) increases), or when many other skills are required for the job j (i.e. when
s ∈S
x(j, s ) increases). RCA provides a method to measure the importance of a skill in a job ad, relative to the total share of demand for that skill in all job ads. It has been applied across a range of disciplines, such as trade economics (Hidalgo et al. 2007 ) (Vollrath 1991) , identifying key industries in nations (Shutters et al. 2016) , and detecting the labour polarisation of workplace skills (Alabdulkareem et al. 2018) .
Measure skill similarity. The next step is measuring the complementarity of skill-pairs that co-occur in job ads. First, we compute the 'effective use of skills' e(j, s) defined as e(j, s) = 1 when RCA(j, s) > 1 and e(j, s) = 0 otherwise. Finally, we compute the skill complementarity (denoted θ) as the minimum of the conditional probabilities of a skills-pair being effectively used within the same job ad. Skills s and s are considered as highly complementary if they tend to commonly co-occur within individual job ads, for whatever reason. Formally: 
Note that θ(s, s ) ∈ [0, 1], a larger value indicates that s and s are more similar, and it reaches the maximum value when s and s always co-occur (i.e. they never appear separately).
Top journalism skills. Following the procedure outlined in (Dawson et al. 2019) for building sets of highly complementary skills, we use the θ function together with 'Journalism' as the 'seed' skill to create top yearly lists of journalism skills. More precisely, we compute θ(Journalism, s) -i.e. the similarity between the skill 'Journalism' and each unique skill that occurs during a given year. Skills on each yearly list are ordered by their descending pairwise skill similarity scores. When inspecting the yearly skill lists, we make two observations. First, the skills in 2012 and 2013 appear of notably lower quality than from 2014 onward. We posit that this has to do with imperfect skills extraction methods during the early years of the BGT dataset. As a result, we decided to measure the top yearly journalism skill sets from 2014 to 2018 (the last available full year of data for which we had access). § Second, we decided to retain only the top 50 skills on each yearly list. Through qualitative analysis, we determined that this threshold of 50 is both sufficiently exclusive for defining journalism skills and reasonably inclusive for detecting the evolution of new, emerging skills in journalism. The purpose of these top journalism skills lists is to capture journalism labour trends; it is not intended to represent a complete taxonomy of journalism skills. The yearly lists of top journalism skills, and their similarity scores, can be observed in the Supplemental Material Sec. Top Journalism Skills by Year.
Compute journalism skill intensity. For the occupational similarity analysis in Sec. Journalism Skills, we decided to use the BGT occupational ontology as opposed to ANZSCO. This is because the BGT occupational classes appear more reflective of current job titles. For example, a job title advertised for a 'Social Media Manager' is classified by BGT as a 'Social Media Strategist / Specialist'. Whereas the same job title would be classified by ANZSCO as an 'Advertising Specialist' or 'Marketing Specialist'.
We use the Prophet time-series forecasting tool developed by Facebook Research (Taylor and Letham 2018). Prophet is an auto-regressive tool that fits non-linear time-series trends with the effects from daily, weekly, and yearly seasonality, and also holidays. The main model components are represented in the following equation:
where g(t) refers to the trend function that models nonperiodic changes over time; s(t) represents periodic changes, such as seasonality; h(t) denotes holiday effects; and t is the error term and represents all other idiosyncratic changes.
We evaluate the forecasting performance using a temporal holdout setup. That is, we split the available time-series into a training part (the first part of the sequence) and a testing part (the latter part of the sequence). We train the Prophet model on the training part, and we generate job ad posting forecasts by "running time forward" in Eq. (5) for time t in the testing period. Finally, we measure the accuracy of the forecast against the observed posting volumes using the Symmetric Mean Absolute Percentage Error (SMAPE) (Scott Armstrong 1985; Makridakis 1993) . SMAPE is formally defined as:
where A t denotes the actual value of jobs posted on day t, and F t is the predicted value of job ads on day t. SMAPE ranges from 0 to 200, with 0 indicating a perfect prediction and 200 the largest possible error. When actual and predicted values are both 0, we define SMAPE to be 0. We selected SMAPE as an alternative to the more widely used MAPE because it is (1) scale-independent and (2) robust to actual or predicted zero values. To evaluate the uncertainty of the forecast, we adopt a 'sliding window' approach. This consists of using a constant number of training days (here 1, 186 days) to train the model, and we test the forecasting performance on the next 365 days. We then shift both the training and the testing periods right by one day, and the process is repeated. Consequently, we train and test the model 365 times, and we obtain 365 SMAPE performance values.
Top journalism skills calculated by skill similarity methodology in Sec. Skill Similarity. 