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Linking Twitter Archives with Television Archives
Abstract
Social media data has already established itself as an important data source for researchers working in a number of different domains. It has also attracted the attention of archiving institutions, many of which have already extended their crawling processes to capture at least some forms of social media data. However, far too little attention has been paid to providing access to this data, which has generally been collected using application programming interfaces (APIs). There is a growing need to contextualize the data gathered from APIs, so that researchers can make informed decisions about how to analyse it, and to develop efficient ways of providing access to it. This chapter will discuss one possible means of providing enhanced access: a new interface developed at the Institut national de l’audiovisuel (INA) that links Twitter and television archives to recreate the phenomenon of the “second screen”, or more precisely the experience of “social television”. The phrase “second screen” describes the increasingly ubiquitous activity of using a second computing device (commonly a mobile phone or tablet) while watching television. If the second device is used to comment on, like or retweet television-related content via social media, this results in the so-called social television. The analysis of this activity, and this data, offers a promising new avenue of research for scholars, especially those based on digital humanities. To the best of our knowledge, the work that will be discussed here is the first attempt at considering how best to recreate the experience of “social television” using archived data.
... By identifying patterns in audience reactions, such as which characters or storylines are most popular or controversial, sentiment analysis can provide valuable insights into how audiences interpret and respond to different aspects of a show (Antonakaki et al. 2021, Giachanou and Crestani 2016, Rocchi 2022a, 2022b, Scharl et al. 2016. Of particular interest is the use of social media as a second screen: second screen engagement allows viewers to share their opinions, reactions, and commentary with a broader audience and to engage in online live conversations around TV shows (Buschow et al. 2014, Pehlivan 2021, Williams and Gonlin 2017. Another approach is to analyze the use of hashtags related to a television show (Pilař et al. 2021). ...
The chapter discusses the use of data-driven approaches in television studies, which has become possible due to the increasing availability of digital data. Computational techniques can be used to analyze cultural artifacts, gain insights into audience reactions to specific shows or episodes, and investigate patterns and trends in television programming over time. The chapter also highlights the challenges of analyzing television series, which are complex open systems that interact with external factors such as the production process, audience feedback, and cultural and social context. Content analysis, which involves qualitative and quantitative methods based on the coding process and data collection, can be used to analyze various elements of a TV series.
Generative AI is also discussed, which refers to the use of deep multi-modal algorithms to generate new content such as images, speech, and text. Generative methods like Generative Adversarial Networks (GANs) and Stable Diffusion can create new content that is almost indistinguishable from real data. While generating videos is more challenging, Recurrent Neural Networks (RNNs) like LSTMs can capture the temporal dynamics of the scenes to create interesting and promising applications for complex, but short-duration videos.
This article examines how the ‘refugee crisis’, sparked by the arrival of refugees from the Syrian civil war and other conflicts around the world, was articulated across Dutch television news programs and social media between 2013 and 2018. This crisis has been described as a key catalyst of the radicalization of European political discourse. Crucially, it took shape during a period of profound transformation of the media landscape, in which mass media lost significant ground to social media as authoritative sources of truth and norms. The research focuses on the crucial but underexplored link between television and social media discourse, which is at the heart of contemporary European public debate. Using a combination of digital methods and NLP techniques, the article compares automatic speech recognition (ASR) transcripts of Dutch televised news on the refugee crisis with responses from publics on Facebook and Twitter. This computational cross-media approach enables a longitudinal analysis of how social media users differ in their interpretation of key events characterizing the crisis, as well as what language is acceptable to debate issues around integration, tolerance and identity. A rejection of mainstream news media editorial guidelines by social media users eventually resulted in their consumption of populist right-wing (‘alternative’) news media and active transgression of anti-discriminatory speech norms.
Social networks have altered how viewers watch television and consume information. This new context has obliged broadcasters to adapt their practices to reach viewers in all platforms. In this article, we focus on how the evening news programmes from the general-interest DTT channels in the five main European markets (France, Germany, Italy, Spain, and the United Kingdom) appeal to their social audience. This concept, although ambiguous, refers to the activity of viewers on social networks in relation to the contents broadcast by the television industry in its multiple forms. We analyse both the screen strategies and their activity on their official Twitter accounts. Although the evening news is the anchor of the prime time and one of the main assets to instil the channels with prestige and influence, the conclusions point to a certain neglect of the social audience from the industry in these key programmes. But mostly, our research reveals how the specificities of the format and the nature of the content distinguish the evening news from other live TV shows.
Television is no longer the king of the living room: 86% of people watch TV with a second screen in the nearby and more than 30% of the attention time is given to the second device to perform social activities. Therefore, the television industry is facing a new challenge: find a way to re-catch viewers’ attention. A recent and popular approach considers the use of official hashtags to implement a cross-media strategy that will connect different contents across multiple media. Since the simple proposition of official hashtags is not sufficient to guarantee the success of a cross media strategy, in this paper, we analyze how official hashtags are used and we propose a model to write tweets effectively. The model is based on the analysis of more than 250,000 tweets that talk about TV-shows. In particular, (i) we analyze the availability and visibility of official hashtags, (ii) we study the tweets characteristics written by the most retweeted authors, and (iii) we build a network of hashtags in order to understand how users use official hashtags. The obtained results allowed us to define guidelines to help broadcasters in the promotion of TV-shows and in the engagement of viewers.
This article describes how TV fans make strategic use of Twitter as a tool for activism to launch " Save Our Show " campaigns and highlights a shift toward a collaborative relationship between fan activists and producers in the context of these campaigns, shaped by deep transformations in the media ecosystem and viewing measurement techniques. Based on participant observation and qualitative content analysis, I explore the case of the Twitter campaign led by a fandom dedicated to FOX's science fiction television series Fringe (2008–13). In my examination, I argue that fans' expert understanding of Twitter's affordances and the audience measurement market are crucial for a series to achieve renewal. In parallel, I suggest that the power negotiation between fans and networks can be substituted by a direct cooperation that indirectly might benefit both creators' labor for the show and advertisers' investments. However, despite this scenario where fans enjoy a better position to influence networks' decisions, their labor on social media may be yet another device for self-commodification and exploitation.
In den vergangenen Jahren hat sich die wissenschaftliche Forschung dem noch recht jungen Phänomen der Second-Screen-Nutzung bereits intensiv gewidmet. Die Frage nach den konkreten Praktiken der Second-Screen-Nutzung, also wie mit den zwei Bildschirmen tatsächlich umgegangen wird, ist dabei bisher noch nicht näher untersucht worden. Für eine solche Forschungsperspektive wirbt dieser Beitrag und bietet einen konzeptionellen Rahmen für eine differenzierte Beobachtung und Beschreibung solcher Praktiken an. Dazu wird auf der Grundlage der bisher vorhandenen Literatur zunächst eine Arbeitsdefinition für Second-Screen-Nutzung entwickelt und aus verschiedenen Ansätzen der Mediennutzungs- und Rezeptionsforschung zentrale Aspekte für dessen Untersuchung herausgearbeitet. Vor diesem Hintergrund werden schließlich verschiedene Praktiken der Second-Screen-Nutzung anhand von Beobachtungen aus einer Studie zur Twitter-Nutzung während der ARD-Krimiserie „Tatort“ beispielhaft beschrieben und Vorschläge für deren weitere Untersuchung unterbreitet.
The use of peripheral devices or second screens to access social media and other content is now a common activity during televised political debates. Based on a study conducted during the 2015 UK General Election debates, this paper explores attitudes and practices around such usage. Through the use of home observations and semistructured interviews of 18 participants, we focus on the motivations that the participants had for using second screens, capturing both fulfilled and unfulfilled needs. Based on the results, we suggest future directions for research that may further support online political discourse and we identify the potential need to rethink the implied hierarchy of the phrase second screens.
The popularity of parallel media usage has increased in Germany recently. Second
Screen describes the use of a second device by television viewers to consume further
content which is related to the programme they are watching. The research objective
of this study was to reveal insights into the media consumption and user behaviour of
football spectators regarding Second Screen services. The survey, which was
conducted among German football supporters, showed that their parallel media usage
was lower while a football match was broadcasted compared to other TV
programmes. However, if supporters used a second device, while watching football,
they were using specific Second Screen services more often. Furthermore, it was found
that football supporters are particularly interested in "functional" services such as
statistics and less into social or even gaming activities. Often more than one Second
Screen service is used while a match is broadcasted.
The merger of television and digital technology allows TV producers to author increasingly complex narratives, which pose new challenges for modern audiences. The prototype presented here is targeted at viewers of HBO's Game of Thrones and utilizes manipulatable, tightly synchronized spatial visualizations to concretize complex character relationships. A preliminary user study was conducted, utilizing the less tightly synchronized, non-diagramatic HBO Go application as an experimental control. Results show that users were able to more accurately identify character relationships after watching segments of the TV drama with the companion app prototype.
Framed by the expansion of a mobility centred technological market, Second Screen applications have become increasingly relevant in recent years. This popularity and the adjoined increase in investment by major TV operators have promoted a broad range of services. A preliminary analysis of the current offering suggests that entertainment and e-commerce products are the most common type of Second Screen apps available. The research question of this paper is thus 'where will these developments take us?'. We will map out the historical background of Second Screen apps, propose a tentative definition and theoretical model for its functioning, and indicate possible convergence points with the journalistic production – an intersection point yet to be explored and with potential for appropriation.
This study focuses on second screening for news, a hybrid media process that combines watching news on television and a second, web-connected screen (i.e., smart-phone, lap-top). Based on U.S.-national, 2-wave panel data, the paper (a) examines people's motivations to engage in second screen use, and then (b) advances the relationship between second screening and online political behaviors. Discussing and pursuing further information are both central motivations for second screen use. Furthermore, results suggest second screening for news is a significant predictor of online political participation and a key link between TV news and political engagement as this relationship is fully mediated. The study advances theoretically and empirically ways in which an informed public opinion may partake of a more engaged democracy.
Hashtags are creative labels used in micro-blogs to characterize the topic of a message/discussion. However, since hashtags are created in a spontaneous and highly dynamic way by users using multiple languages, the same topic can be associated to different hashtags and conversely, the same hashtag may imply different topics in different time spans. Contrary to common words, sense clustering for hashtags is complicated by the fact that no sense catalogues are available, like, e.g. Wikipedia or WordNet and furthermore, hashtag labels are
often obscure. In this paper we propose a sense clustering algorithm based on temporal mining. First, hashtag time series are converted into strings of symbols using Symbolic Aggregate ApproXimation (SAX), then, hashtags are clustered based on string similarity and temporal co-occurrence. Evaluation is performed
on two reference datasets of semantically tagged hashtags. We also perform a complexity evaluation of our algorithm, since efficiency is a crucial performance factor when processing large-scale data streams, such as Twitter.
In this paper, we review recent networking developments that will help create the next-generation social television experiences. These include revisiting the way networks are created and using social connectivity to drive physical connectivity and network virtualization. Multipath dissemination and reduction of interruptions will provide better quality of experience. Content protection and privacy are also essential to enable social commentary and metadata applications and will be briefly introduced. Examples of potential applications and results of field trials are also included.
This article analyzes 3 months of online debate during the electoral campaign for the 2016 Italian constitutional referendum. Through supervised sentiment analysis, we assess the extent of support for the referendum within the general public of Twitter users (Twittersphere) by analyzing the voting intentions expressed online in 2,369,333 tweets. Similarly, we exploit the practice of social TV and investigate the support for the referendum expressed by the 160,465 tweets posted by second screeners, that is, the subsample of Twitter users who watched and actively commented on nine political talk shows during the campaign. We compare the mentions and the attitudes of the Twittersphere and the second screeners by means of a lead–lag analysis to test whether the second screeners can act as influencers and trendsetters able to shape or anticipate attention and opinions toward an issue within larger audiences. The results reveal an inverse relationship between the Twittersphere and the second screeners whereby the reactions of the latter diverge from those of the general Twitter public. This finding has implications for the literature on echo chambers and the polarization of social media.
To attract and retain a new demographic of viewers, television producers have aimed to engage audiences through the “second screen” via social media. This paper concerns the use of Twitter during live television broadcasts of a panel show, the Australian Broadcasting Corporation’s political and current affairs show Q&A, where the TV audience can post tweets, some of which appear in a tickertape on the TV screen and are broadcast to all viewers. We present a method for aggregating audience opinions expressed via Twitter that could be used for live feedback after each segment of the show. We investigate segment classification models in the incremental setting, and use a combination of domain-specific and general training data for sentiment analysis. The aggregated analysis can be used to determine polarizing and volatile panellists, controversial topics and bias in the selection of tweets for on-screen display.
This chapter reviews the current state of media management scholarship and the theoretical approaches present in the current body of literature. It is guided by the following questions: What theoretical body of knowledge has been used in media management literature? What are the major advances since 2006? What areas of concern should guide research over the next decade? It closes with a discussion about the theoretical research agenda of the field.
In a short few years, social media has become the dominant way in which we communicate with the outside world. It has become prevalent in almost every aspect of our daily lives, but one of the most significant changes social media has had, has been on the way we watch television. This phenomenon, known as dual screening, has caused some concern amongst marketers and advertisers, who believed that this behaviour was having an overall negative impact on consumer engagement with television. This chapter attempts to address some of these concerns by providing evidence obtained from the neurosciences and from a case study. The evidence we present in this chapter demonstrates the opposite effect, whereby social media can actually be used to enhance viewer engagement.
We often think of TV watching as the activity where people are fully engaged and immersed in the TV program. However, research has shown that there is a continuum of levels of attention while watching TV. We set out to understand multitasking behaviors as well as users' motivation and intention behind simultaneous tasks performed in front of the television. We conducted an in-home qualitative research methods study inside ten households across the San Francisco Bay Area and used a quantitative method for analysis of the large amount of behavioral data we gathered. We recorded participants' television watching behaviors using cameras that were placed in their homes and used retrospective interviews to gather purpose behind events that were observed in the video recordings. We defined eye gaze elsewhere than on the TV as accounting for a multitasking event. It was found that multitasking occurred almost 40% of the time when people were seated in front of the television. Most multitasking occurred during TV programs -- not during the interval between TV programs. Of the time people spent multitasking, 36% was spent on a device, mostly a smartphone. However, only 10% of device-related multitasking was related to the content being played on the TV. With our study, we contribute to the greater body of foundational knowledge around common multitasking behaviors that are conducted in front of the television.
We present "Snapscreen", a prototype second-screen app. Snapscreen is a platform that allows content providers (TV channels, broadcasters) to offer transparently content-related information and services to users watching TV. Users need only install the app on their mobile devices and can then take a snapshot of TV content they are currently watching. The resulting "snap" image is processed by the app to generate an identification key that is sent to the Snapscreen server, where it is matched to TV content in real time. Once a specific program/TV station has been identified, information and services related to this content are sent back to the user for interaction.
Thus, Snapscreen can bridge television and Internet intuitively by using the television content detected to form the basis of an Internet query. An advantage of Snapscreen (over most state-of-the-art apps) is that this single app can offer access to a variety of interactive services and can link to a wide range of content offered by any television channel (station, broadcaster).
In a short few years, social media has become the dominant way in which we communicate with the outside world. It has become prevalent in almost every aspect of our daily lives, but one of the most significant changes social media has had, has been on the way we watch television. This phenomenon, known as dual screening, has caused some concern amongst marketers and advertisers, who believed that this behaviour was having an overall negative impact on consumer engagement with television. This chapter attempts to address some of these concerns by providing evidence obtained from the neurosciences and from a case study. The evidence we present in this chapter demonstrates the opposite effect, whereby social media can actually be used to enhance viewer engagement.
Social TV is the use of communication devices to connect with family and friends watching other TV screens. Plausible arguments suggest both positive and negative effects of social TV viewing on ad-effectiveness. This study contributes by providing evidence for the direction of social TV's effects. The results of a controlled laboratory experiment suggest that the benefits of social TV, principally its association with live TV and therefore less ad-avoidance, come at the cost of negative distraction effects. Like normal coviewing, social TV viewing distracts from ad-processing, reducing unaided recall and brand attitude favorability, compared to individual (solus) viewing. However, social TV messaging about ads improved brand attitude. Perceived creativity increased the likelihood of ad-related messaging. Social TV also has an additional source of distraction, multitasking, but in this study, multitasking did not further reduce ad-effectiveness compared to coviewing. The paper concludes with implications for advertisers and future research.
The increasing popularity of social interactions and geotagged, user-generated content has transformed the television viewing experience from laid-back video watching behavior into a "lean-forward"' socially engaged experience. This article describes a multiscreen, social TV system integrated with social sense via a second screen as a novel paradigm for content consumption. This new application is built upon the authors' cloud-centric media platform, which provides on-demand virtual machines for content platform services, including media distribution, storage, and processing. The media platform is also integrated with a Big Data social platform that crawls and mines social data related to the media content. Specifically, this new social TV approach consists of three key subsystems: interactive TV, social sense, and multiscreen orchestration. Interactive TV implements a cloud-based, social TV system, offering rich social features; social sense discovers the geolocation-aware public perception and knowledge related to the media content; and multiscreen orchestration provides an intuitive and user-friendly human-computer interface to combine the two other subsystems, fusing the TV viewing experience with social perception. The authors have built a proof-of-concept demo over a private cloud at the Nanyang Technological University (NTU), Singapore. Feature verification and performance comparisons demonstrate the feasibility and effectiveness of the proposed approach in transforming the TV viewing experience.
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