IASSI Quarterly: Contributions to Indian Social Science, Vol. 42, No. 4, 2023 Perspectives on Emerging Trends and Technologies in Digital Journalism Debastuti Dasgupta and Alok Kumar Sahai* Journalism has seen a sea change in the way data and information are gathered, processed, produced, distributed and consumed. This calls for novel and more efficient ways to process and distribute news content. With the shortened attention spans and a multitude of offerings, only the most attractive and captivating content will find takers and the associated advertising revenues. New-age technologies such as artificial intelligence, machine learning, robotics, virtual reality and augmented reality have automated the news and entertainment content creation process. With the rise and popularity of interactive and immersive content and social media publishing, consumers have become co-creators of content. The miniaturization of consumer electronics has reduced the size of screens while multiplying the number a million times. Artificial intelligence has enabled micro-targeting of the consumer as per his choice while VR/AR provide an immersive experience. Digital tracking of consumers makes it possible to change the style and flavour of the content. Already AI applications like Chat GPT have started creating content and by 2050 AI-enabled writing and reporting might be the norm. This paper presents a panoramic view of the emerging trends and technologies taking place in the field of journalism. Keywords: I. Artificial intelligence, Virtual reality, Augmented reality, Robotic journalism, Blockchain, Chat GPT INTRODUCTION Information touches our everyday lives in more than one way. A flurry of messages calls for our attention all day long. Global news, current affairs, traffic, sports fixtures, and financial updates are coming from all directions. Our sensory organs of eyes and ears are constantly barraged by a multitude of threads of news ranging from simple text messages to highly complex multimedia messages. Even if we are not looking for news it comes to us often creating information overload and deluge (Shenk, 1997). This marks a sea change, in the way news media is consumed today, brought * Assistant Professor, Department of Journalism and Mass Communication, Asutosh College, Kolkata. Email: debastuti.dg@gmail.com and Associate Professor, Faculty of Management Studies, Sri Sri University, Cuttack. Email: alok.s@srisriuniversity.edu.in, respectively. Perspectives on Emerging Trends and Technologies in Digital Journalism 859 about by the modern digital era of communication. Previously users accessing some information or news would make some efforts to search for the same whether at the corner newsstand or tuning into the scheduled broadcast media at the appointed hour. Television and radio were the places where the family would gather in the drawing rooms to consume the programming as per the time schedules. The viewers or the listeners had little control over the media content dished out by the newspapers, radio or television and the audience could only choose to consume or skip the programme/news. The audience was captive for the programmers and the schedulers or programmers ruled the day. The digitalization of information and satellite communication in the past decades has completely changed the vintage distribution methods and rules of journalistic, commercial and entertainment media content. Today the choice of the media to consume is in the hands of each one of us. The place, format and content are decided by the consumer of news alone and the scheduler and programmers of content are now chasing the audience which means advertising dollars. While the users benefit from the increased scope and content variability, they also benefit from the content targeting. Advances in new technologies such as artificial intelligence (AI) help in this micro-targeting of the consumers of news. AI is at the core of the bunch of new technologies driving the new age of contemporary digital journalism (Newman, 2017). Powering all the digital output platforms and devices, these technologies let the content creators and distributors tailor their offerings as per the preference and consumption pattern of each consumer. Technology has therefore allowed profiling of the interests of the end-users with clinical precision marking a great advancement for content providers. The consumers are given to believe that they are searching and choosing content when in fact they are manipulated by artificial intelligence and algorithmic targeting of content. Artificial intelligence-based technologies provide journalistic, advertising and commercial content to the users based on their past preferences targeting their tastes and likings. Contemporary media consumers are all enveloped by a sea of information. II. INTERNET OF THINGS (IOT) AND THE EVOLUTION OF NEWS Information technology has bridged the gap between people and the need for information. The digitalization of technologies in the last three decades has transformed media content, the field of journalism, news production houses and even consumers (Salaverría and Sádaba, 2003). In the last decade of the 20th century and the first of the twenty-first century, digital technologies have metamorphosed the production processes largely and caused a major disruption in the media business models and journalist profiles. 860 IASSI Quarterly: Contributions to Indian Social Science To understand modern journalism, it is imperative to understand the disruptive technologies involving IoT such as big data analysis, machine learning, artificial intelligence, remote control of electronic systems and data capture systems among others (Greengard, 2015). A few years ago, they would be dismissed as science fiction, but IoT technologies today take centre stage in robotic mechanization and artificial intelligence systems. The extent of the impact of IoT on digital journalism might not be easy to estimate but there can be little doubt that it would be huge and wide-ranging. This is because IoT touches the three legs of journalism namely, gathering, processing and collating the information and distributing the content. The gathering of information will be much denser and more efficient with the multitude of bytes collected from millions of sensors present in small handheld digital devices. High-end Samsung mobile phones have been used successfully by mainstream TV news reporting by several national channels. The enormous amount of data on global temperature, climate, vehicular traffic, pollution, accidents and insurance data is known as Big Data due to the enormity and scale of the data. Big Data has become the major data source for journalists besides traditional sources of information such as interviews, personal observations or secondary and primary data. Information processing employs IoT technologies in a big way. Natural Language Processing is a frontline area where IoT has made its mark of usefulness. Natural Language Processing is an amalgamation of computing technology, linguistics and artificial intelligence and is being used to establish and facilitate communication between humans and computers. These technologies sit at the heart of chatbots and applications that use automatic writing on texts (Veglis and Maniou,2019). The IoT applications have led to algorithmic journalism (Dörr, 2016), and are expanding the scope of technology in newsrooms, springing novel challenges for journalists to adapt to the role of such technologies as full communicating and mediating as well (Lewis et al., 2019). News distribution and dissemination is the third area affected by IoT. The manifold increase in the number of mobile smartphones has taken a new dimension and the scale of news and media consumption has reached a new height (MartínezCosta et al., 2019). In the modern digital ecosystem, all digital devices are seamlessly connected and interact with each other. The machines get in touch with each other and continuously exchange information, churning out data suitable for consumers (Pavlik, 2014). Perspectives on Emerging Trends and Technologies in Digital Journalism 861 III. DIGITAL TECHNOLOGY IN PRODUCTION AND CONSUMPTION Technology has changed the way news is compiled and distributed. Before radio and television made their appearance in the twentieth century, newspapers were the most popular sources of information (Smith, 1980), but modern news media eclipsed the popularity of newspapers as a media. Internet and the spread of internet technologies have marked the certain demise of newspapers and news consumption patterns and habits. Circulations of national dailies have been affected and in a survival response, most national dailies have moved to subscription-based digital deliveries on the internet. The spike in the number of digital interfaces such as laptops, tablets and affordable smartphones has opened newer ways to communicate, deliver and consume the news and allied content. However, as the consumers are now shared by all content providers equally through digital delivery, the producers have to struggle more to find a profitable revenue model. News organizations have struggled to maintain their revenue streams and the competitiveness and relevance to the consumer depend largely on the quality of information content delivered. Newer technologies such as augmented reality (AR) and virtual reality (VR) are marking the next wave of change in immersive content delivery marking the digital transformation of society and the economy (Hassan, 2019). Additionally, there are other front-runner technologies driving innovations in the newsroom such as drones, wearable technologies, interactive and visual storytelling and news bots to name a few. IV. EVOLUTION OF NEWER FORMS OF JOURNALISM The major technology that created a major impact was radio communications with handheld devices. The handheld radios or walkie-talkies kept the editors with reporters as the story unfolded. The nascent technology that was adopted for commercial communications after WWII was used widely by US newspapers (Mari, 2018). The present-day reporting from the scene of the war zone is a more advanced form of radio communication now helped by the internet and satellite radios. By the middle of the last century, newspapers were almost fully automated and radio communication, battery-operated recorders, radio cars and telephones changed and strengthened the work routines of the newsrooms of the era (Mari, 2018). The technologies of the day shaped the news content and the formats in which they could be presented. What we are seeing now is only a change of episode and scale with technologies like AI, ML, advanced computing and robotics doing what telephone, telegraph, automobile and radio communication did decades ago. Computers made their presence felt in journalism in the 1950s (Cox 2000) but it was not until the early 862 IASSI Quarterly: Contributions to Indian Social Science 1990s that extensive deployment of data changed the very way journalism was practised or known. Meyer (1973) predicted that precision journalism or computerassisted production of content would make significant headway in newsrooms across the board. Coddington (2015) called it data journalism. The internet has democratized access to databases, resources, tools and information content to all. The usefulness of data journalism within the ambit of the whole ecosystem of news production needs to be realized by production houses. The multi-device multi-point data journalism is capable of bridging the gap between technological advancement on one side and newsroom journalists on the other side. It can expand and widen the horizons of the processes and practices of journalists to have a deeper understanding of relevant things. Robotic journalism is yet another emerging facet of modern digital journalism (Lemelshtrich, 2018). Automated journalism can be illustrated with the help of a scenario where the machine could convert data into a news item without much or any human interference. Such technologies are being developed by technology companies that are far removed from traditional media companies. The convergence of digital and communication technologies with generous inputs from semantics, natural language processing and machine learning has led to a product that is causing and creating disruptive advancements in media production and automation. (Caswell and Dörr, 2017). News organizations the world over have resorted to automatic news drafting technologies. The technology behind these automatic writing robots is called natural language generation (NLG) which creates content automatically from digitally structured data (Carlson, 2015). However robotic journalism has found its widest use in sports and financial reporting for the simple reason of the data-driven reporting in these sectors. With the rapid strides made by AI, ML and IoT technologies, we might see robotic journalism and reporting take up complex stories too (Caswell and Dörr, 2017). On the positive side, any new advancement in productivity means more production, more efficiency and lower costs which in today’s competitive times is any day a welcome sign. The coverage decision in any newspaper is decided by the limited availability of staff and space to include newsworthy ideas to maximize the pull of the consumers (Carlson, 2015). Robotic journalism can thus not only increase the coverage scope cost-effectively but also affect the conditions of news reporting, filling the news items automatically as it happens. The advances in technology have allowed publishing houses to create novel forms of multimedia content. Autonomous video creation software systems automatically combine and compile text, pictures and videos in the form of new deliverables. Increased automation seems essential to the Perspectives on Emerging Trends and Technologies in Digital Journalism 863 practice of journalism in the times to come. These technological tools are not only able to access information but also provide a wealth of useful audience data to advertisers. To sum up, technology can switch the power equations between the stakeholders involved in technology development and newsroom innovations. Innovation in news production traditionally has happened outside and then was adopted by a process called technology diffusion (Belair-Gagnon et al., 2017). Unmanned aerial vehicles or drones are being increasingly used in disruptive journalistic reporting and find their use in producing long video shots for the scenes of reporting. Drones were not developed specifically for newsroom applications but they are now increasingly being used for the same. News media first deployed drones in 2011 in Warsaw during the riots (Lauk et al., 2016). Drones have held considerable promise and potential to provide gains in productivity with large cost savings in gathering data in action journalism. Drones provide surveillance capabilities and reduce the risk of human exposure in hazardous situations. Advanced drone control technology has found its way to consumer electronics and news publishing houses now have a cost-effective and efficient means of digital data gathering through visuals. V. PERVASIVE DIGITAL JOURNALISM The Internet has commoditized information. Social media networks in the last few years have shown the participatory culture of the common people (Jenkins et al., 2013). Social media networks also have shown a linkage and influence on what is called ubiquitous journalism or some kind of citizen journalism which is an entirely new way of distributing information and news content. Twitter has emerged as a commonly used tool for journalists of all colours and creeds to instantly report breaking news events either as print or as pictures and videos. Trending threads follow on top of the lot allowing everyone to add his reactions making the whole media distribution interactive. Even government and business organizations have taken to Twitter for quicker grievance handling besides posting relevant data of interest. The current Covid guidelines and the daily infected morbidity and mortality rates are being published several times a day. Social media offers high visibility at a low cost to ubiquitous digital journalism (Uskali, 2018). New devices such as smartwatches and smart speakers are going to change the way news and media are consumed. These interactive devices enabled with artificial intelligence can double up as a radio with voice command interactive immersive experience. Smart speakers can augment or replace normal radio broadcasts with a conversational treat (Bullard, 2019; Newman, 2018). In the US only 18% of owners used smart speakers daily to listen to the news while 22% tuned into podcasts. Already 864 IASSI Quarterly: Contributions to Indian Social Science users are complaining about the lack of variety in programming and there is a huge untapped demand in this form of content delivery. The prospect of engaging with the listener builds on the success of the numerous FM channels that allow engagement of the audience. Media providers can now customize their offerings to the taste of individual customers in a way that is more engaging and riveting (Bullard, 2019). Immersive journalism is an offshoot of post-mobile technologies such as augmented reality (AR) and virtual reality (VR). Around 2016, VR and AR provided a new format of storytelling where the audience could have a firsthand immersive feel of the events as they happened. The immersive experience is the high point of VR technology which brings a new wave of digitally-enhanced video experience of the economy, society or culture. The experience could be immersive and interactive taking the viewer through a 360-degree view of the content giving them the experience of being in the middle of things (Terdiman, 2018; Mabrook and Singer, 2019). Shot with multiple cameras angles these videos are emotionally impactful and engaging new forms of filming (Hassan, 2019; Mabrook and Singer, 2019). Augmented reality offers another type of immersive journalism. AR offers to promise an attention-grabbing experience through a semi-real world where the technology brings and builds a reality into the story. VI. UBIQUITOUS JOURNALISM Technological advances have driven journalism to a new frontier that can be labelled as ubiquitous journalism. This is an emerging form distinguished by the expanded methods of production and consumption of personalized information content with extensive employment of technology to cater to a wide audience on all kinds of digital devices. Starting with the digitalization of media the technologies have taken journalism through participative journalism and robotic production of content is already here. Journalism has come far from the classic media outlets of the old press, radio, television and internet and any personal digital device today is a media platform. Ubiquitous journalism is marked by some essential features namely, i) expanded news production by journalists, users & robots, ii) digital access to the content, iii) flow of information without time or space restrictions, iv) AI-based personalized distribution of content and, v) Immersive news storytelling using VR and AR. There is a possibility of combining a few or all five elements to create myriad possibilities of media offerings. VII. ALGORITHMIC JOURNALISM News written automatically is already a reality and the quality of content is also improving. Content created by the machines started with meteorological reporting over half a century ago and was included as a snippet in the daily news (Meehan, 1977; Glahn, 1970). The last decade of the 20th century marks the advent of automated news with the development of hardware and software resources to generate financial news Perspectives on Emerging Trends and Technologies in Digital Journalism 865 content that was offered to a portfolio of clients which included names such as Reuters and New York Financial Press (Winkler, 2014) to name a few. The origin of the automation of content creation can be traced back to the days of data journalism or what was popularly known as computer-assisted reporting (Gynnild, 2014). The 21st century ushered in new ways the data was visualized. Los Angeles Times then in 2007 launched the Quakebot, an algorithmic bot to track the seismic data received from the seismograph to prepare reporting as per a predefined template. The exercise by the LA Times not only computerized the news but also provided for automatic publication of news of an earthquake if the magnitude of the earthquake was less than six. Below 6 magnitude earthquakes are routine and do not cause such damage as to merit a full-blown news story. The important and noteworthy transformation, in this case, is from an analytical algorithm to a creative algorithm. This is the path of evolution of digital media, characterized by the semantics of the web interface and simultaneous application of AI/ML applied to robotic advancements in the newsrooms. This marks the transition and passage from data journalism to computer journalism. “Computational journalism works primarily through the abstraction of information to produce computable models, while data journalism works primarily through the analysis of data together to produce data-oriented stories” (Stavelin, 2014). VIII. BIG DATA JOURNALISM Automated journalism became possible through the intersection of journalism and Big Data (Carlson,2014). While computers can retrieve and process data at lightning speed, Big Data can be mined for useful hidden information in unstructured information silos (Wölker and Powell,2018). Big Data and computer integration also allow interactivity between consumers and news producers and providers (Flew et al., 2012). The start of the robotization of news can be traced to the computerization of the newsroom. The computers replaced typewriters and news reception systems were computerized as technological advancement arrived at the scene. Big Data is therefore an umbrella term for several strategies and tricks involving huge data sets and associated technologies that extract meaningful insights from this vast amount of data. The Big Data trend has created an impact in the media industry like other industries as new technologies are being developed to simplify and automate the data analysis process. For the media industry, Big data can be defined by the four V’s, namely Volume of the data; Velocity of data (speed is of utmost importance in news); Variety of the structured and unstructured formats of reporting and Value for the journalistic 866 IASSI Quarterly: Contributions to Indian Social Science content suited to draw the consumers and the advertising revenues. as contrasted with Little Data that can be stored on personal computers or company servers, Big Data places huge demands on data storage offered by the cloud alone. Google and YouTube process over 24 petabytes of Big Data every day. A petabyte (one million GB) could store over 13 years of continuously running HD videos. IX. NOVEL PRODUCTIVE ROUTINES Recent developments in the production of news employ natural language generation (NLG) which is a subfield of natural language processing. Terms like machine journalism, robotic journalism, automated journalism and algorithmic journalism have now abundantly appeared in the mainstream media and scientific discourse. With the rising coverage and abundance of digital and digitalized data, NLG is defined as a product of computers and software systems that automatically produce content in human language from a computational presentation of information as data (Reiter and Dale, 2000). Preliminary studies on comparisons of perceived quality and credibility of algorithmically produced content have failed to show discernible differences between machine-generated and human-generated content (Van Der Kaa and Krahmer, 2014). NLG and its technical functionality and feasibility are tested within the framework of the input- throughput-output or I-T-O model (Latzer et al., 2014). Latzer et al. (2014) identified algorithmic selection as the functional and technical basis of many software applications. NLG is not a new research field and actually was born in the 1950s as a minor part of machine translation (Reiter, 2010). It developed as a major research tool in the 1980s. The language generation processes gradually advanced and progressed with the availability of data availability and the growing importance of statistical analytics. Popularly known example was the text-based weather forecast, medical (Portet et al., 2007), sports (Robin and McKeown, 1996), financial (Kukich, 1983) or the reporting of engineering data (Yu et al., 2007). Latzer et al. 2014) define the I-T-O model of algorithms as a finite set of precisely defined software steps or stages that transform inputs (I) through pre-specified computational procedures (throughput- T) into output (O). Depending upon the applications under consideration Latzer et al. (2014) define the basic framework of the algorithmic selection on the net where a set of rules is used to pick and process the available raw data as feed and transform them into consumable journalistic reporting as output. X. BOTS AND ALGORITHMS IN THE NEWSROOMS Artificial intelligence imitates human intelligence by way of computational processes which are based on machine learning behaviour to interpret a stimulus and then Perspectives on Emerging Trends and Technologies in Digital Journalism 867 respond accordingly. The inclusion of AI and ML in mass media and communication content generation is marked by a sudden implosion of data from the numerous digital devices producing content 24x7. The vast amount of raw data pouring in from all sources which even includes the consumers of content needs enormous processing power of computers to process and draw meaningful insights for the consumers of news content. Graefe (2016) pointed out that once an algorithm was designed and put in place, it was capable of being programmable, and adaptive to minor tweaks to automatically generate textual journalistic content or graphical and multimedia content from the data. AI bots such as Chat GPT are already surprising many content writers in various fields including journalistic reporting. Four interesting things need to a mentioned here namely, i) the ability of artificial intelligence to substitute the cognitive part of journalistic work, ii) database preparation, iii) the creation of algorithms and iv) the possible generation of false and incorrect stories by the robots. Computers and algorithms have brought the objective ability to analyze, collate, curate and narrate content. XI. JOURNALISM IN THE FUTURE The digital revolution holds big challenges for the journalists such as how to morph the content for an audience challenged with a short attention span and how to choose the technologies to put the money on. To survive and thrive in the new digital media environment, editors and producers will have to reinvent their art and rediscover their work of collecting, processing and distributing news content. Journalism needs to evolve to keep pace with the ever-changing data landscape and the changing tastes of the audience. The producers have tailored their content offering to the laptop format while the audience has chosen to consume 50 per cent of content on their mobile phones. There need to be three-four or five default formats and one that is best suited for any story will have to be used on the fly. The whole notion of the creation of content, production schedules and delivery platforms has changed dramatically. XII. CONCLUSION Regardless of the speed of change the print, broadcast and digital media will be confronting the challenges and opportunities thrown by the amount of data and the newer technologies. These disruptive technologies include artificial intelligence, robotics, virtual reality, augmented reality, blockchain, 3-D printing and driverless cars. Blockchain is the latest but least understood and exploited technology by media production houses. Blockchain is a shared non-mutable ledger for the recording of the history of transactions.it is expected that blockchain in media is likely to grow from $51 868 IASSI Quarterly: Contributions to Indian Social Science million to $1 billion by 2023. That translates into a compounded annual growth of 81%. Blockchain-enabled applications will help improve the production and dissemination of content and prevent piracy, unauthorized and illegal file sharing and intellectual property rights management. Blockchain-based licensing platforms such as Publica are helping authors distribute their work. Blockchain-based licensing and distribution solutions can connect authors with publishers while owning the content themselves. Emerging technologies have offered both opportunities and challenges to journalists and journalism calling for strategic decision-making to make headway. 5G connectivity, immersive audio-visual content, VR/AR, AI/ML and narrative automation are the newer frontiers of exploration to continue the good old storytelling with the latest adoption of technologies as they evolve. References Belair-Gagnon V, Owen T, Holton A.E. (2017) Unmanned aerial vehicles and journalistic disruption. Digit J 5(10):1226–1239 Bullard, G. (2019) Smart speaker use is growing. Will news grow with it? Nieman reports. Retrieved13 Mar 2021, from https://niemanreports.org/articles/reimagining-audio-news/ Cairo, A. (2016) “The functional art”. New Riders Publishing, Berkeley Carlson,M. (2014) The robotic reporter: automated journalism and the redefinition of labor, compositional forms, and journalistic authority. Digit J 3(3):416–431. https://doi.org/10.1080/21 670811.2014.976412 Carlson, M. (2015) The robotic reporter: automated journalism and the redefinition of labor, compositional forms, and journalistic authority. Digit J 3(3):416–431 Castillo, A, Thierer AD (2015) Projecting the growth and economic impact of the internet of things. Mercatus Center Caswell, D,,Dörr K.(2017) Automated journalism 2.0: event-driven narratives. J Pract 12(4):477–496 Coddington, M. (2015) Clarifying journalism’s quantitative turn. Digit J 3(3):331–348 Cox, M. (2000) The development of computer-assisted reporting. Newspaper division. Assoc Educ J Mass Commun SE Colloquium 2030(305):22 Cunningham, S.D., Turnbull, S. (2014) The media and communications in Australia, 4th edn. Allen & Unwin, Sydney Dörr, K.N.(2016). Mapping the field of Algorithmic Journalism. Digital Journalism, 4(6):700-722 Flew, T, Christina Spurgeon, A.D., Swift A (2012) The promise of computational journalism. J Pract6(2):157–171. https://doi.org/10.1080/17512786.2011.616655 Glahn, H.R. (1970) Computer worded forecasts. Bull Am Meteorol Soc 51(12):1126–1132. Graefe, A. (2016) Guide to automated journalism. Retrieved from https://www.cjr.org/tow_center_ reports/guide_to_automated_journalism.php Greengard, S. (2015) “The internet of things”. MIT Press, Cambridge Hassan R (2019) Digitality, virtual reality and the ‘Empathy Machine’. Digit J (Online first, 2 Jan) Perspectives on Emerging Trends and Technologies in Digital Journalism 869 Gynnild, A. (2014) Journalism innovation leads to innovation journalism: the impact of computational exploration on changing mindsets. Journalism 15(6):713–730. https://doi. org/10.1177/1464884913486393 Hermida, A, Young, M.L. (2017) Finding the data unicorn. Digit J 5(2):159–176 Jenkins, H, Ford, S, Green, J. (2013) “Spreadable media: creating value and meaning in a networked Culture”. New York University Press, New York Kukich,, Karen. (1983). “Design and implementation of a knowledge`based report generator.” Proceedings of 21st Annual Meeting of the Association for Computational Linguistics, 145–150. Latzer,,Michael, Hollnbuchner, Katharina, Just,Natascha, Saurwein, Florian (2014).The economics of algorithmic selection on the Internet. University of Zurich, Zurich.Online:http://www. mediachange.ch/media//pdf/publications/Economics_of_algorithmic_selection_WP.pdf Lauk, E, Uskali, T, Kuutti, H, Hirvinen, H. (2016) Drone journalism: the newest global test of pressfreedom. In: CarlsonU(ed) Freedom of expression andmedia in transition: studies and reflectionsin the digital age. Nordicom, Gothemburg, pp 117–125 Lemelshtrich, L.N. (2018) Robot journalism: can human journalism survive?. World Scientific Publishing, New Jersey Lewis, S.C., Guzman, A.L., Schmidt, T.R. (2019) Automation, journalism, and human–machine communication: rethinking roles and relationships of humans and machines in news. Digit J (Online first, 23 Apr) Lozano Bartolozzi P. (1974) El ecosistema informativo. Introducción al estudio de las noticias internacionales. EUNSA, Pamplona Meyer, P. (1973) “Precision journalism: a reporter’s introduction to social science methods”. Indiana University Press, Bloomington Mabrook, R, Singer, J.B. (2019) “Virtual reality, 360° video, and journalism studies: conceptual approaches to immersive technologies”. J Stud (Online first, 17 Jan) Mari, W. (2018) “Technology in the newsroom”. J Stud 19(9):1366–1389 Martínez-Costa MP, Salaverría R, Breiner J (2019) El ecosistema que viene. In: López García X, Meehan, J.R. (1977) TALE-SPIN, An interactive program that writes stories. Int Jt Conf Artif Intell77(1):91–98. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/ summary?doi=10.1.1.74.173 Meyer, P. (1975) Precision journalism. Commun Inf 1(1):164–165 Newman, N. (2017) “Journalism, media, and technology trends and predictions 2017”. Oxford Reuters Institute for the Study of Journalism Newman, N. (2018) “The future of voice and the implications for news”. Oxford Reuters Institute for the Study of Journalism Pavlik, J.V. (2014) Ubiquidade: O 7º princípio do jornalismo na era digital. In: Canavilhas J (Org) Webjornalismo: 7 caraterísticas que marcam a diferença. Livros LabCom, Covilhã, pp 159–183 Portet, François, Ehud Reiter, Jim Hunter, and Somayajulu Sripada. (2007). “Automatic generation of textual summaries from neonatal intensive care data.” Proceedings of the 11th Conference on Artificial Intelligence in Medicine (AIME 2007),227–36 Reiter, Ehud. (2010). “Natural Language Generation.” In The Handbook of Computational Linguistics and Natural Language Processing, edited by Alexander Clark, Chris Fox,and Shalom Lappin,574–598. Oxford:Wiley`Blackwell. 870 IASSI Quarterly: Contributions to Indian Social Science Reiter, Ehud, and Robert Dale. (2000). “Building Natural Language Generation Systems”. Cambridge University Press Robin,Jacques,and Kathleen R.McKeown (1996).“Empirically designing and evaluating a new revision`based model for summary generation.” Artificial Intelligence (85) 1`2: 135–179. Salaverría, R, Sádaba, C. (2003) Towards new media paradigms: content, producers, organisations and audiences. Ediciones Eunate, Pamplona Salaverría, R. (2017) Allá donde estés, habrá noticias. Cuad de Periodistas 35:15–22 Shenk, D. (1997) Data smog. Surviving the info glut. Technol Rev 100(4) Stone, M. L. (2014). Big Data for Media. Reuters Report. Reuters Institute for the Study of Journalism. Terdiman, D. (2018) Why 2018 will be the year of VR 2.0. Retrieved from https://www.fastcompany. com/40503648/why-2018-will-be-the-year-of-vr-2-0 Uskali, T. (2018) Towards journalism everywhere. In: Daubs MS, Manzerolle VR (eds) “Mobile andubiquitous media: critical and international perspectives”. Peter Lang, New York, pp 237–247 Van der Kaa, Hille, and Emiel Krahmer. (2014). “Journalist versus news consumer: The perceived credibility of machine written news.” Research Paper presented at the 2014 Computation Journalism Symposium, Columbia University, New York. Online:http://compute`cuj.org/ cj`2014/cj2014_session4_paper2.pdf. Veglis, A, Maniou, T.A. (2019) Chatbots on the rise: a new narrative in journalism. Stud Media Commun 7(1):1–6 Yu, Jin, Ehud Reiter, Jim Hunter, and Chris Mellish (2007). “Choosing the content of textual summaries of large time`series data sets”.Natural Language Engineering(13) 1: 25–49. Winkler, M. (2014) “The bloomberg way: a guide for reporters and editors”. Wiley, New Jersey Wölker, A, Powell, T.E. (2018) Algorithms in the newsroom? News readers perceived credibility and selection of automated journalism. Journalism (Online first, Feb 18).