Understanding the Emotional Impact of GIFs on Instagram through Consumer Neuroscience

The ability of GIFs to generate emotionality in social media marketing strategies is analyzed. The aim of this work is to show how neuroscience research techniques can be integrated into the analysis of emotions, improving the results and helping to guide actions in social networks. This research is structured in two phases: an experimental study using automated biometric analysis (facial coding, GSR and eye tracking) and an analysis of declared feelings in the comments of Instagram users. Explicit valence, type of emotion, length of comment and proportion of emojis are extracted. The results indicate that the explicit measure of emotional valence shows a higher and more positive emotional level than the implicit one. This difference is influenced differently by the engagement and the proportion of emojis in the comment. A further step has been taken in the measurement of user emotionality in social media campaigns, including not only content analysis, but also providing new insights thanks to neuromarketin

Sentimental analysis in Instagram: polarity and subjectivity of children’s accounts

Instagram se ha convertido en parte integral de la vida cotidiana de niños y jóvenes, gestando una suerte de álbum familiar. En este escenario, analizamos la polaridad y subjetividad de 772 entradas de texto de cuentas infantiles gestionadas por padres en la plataforma mediante procesamiento del lenguaje natural con machine learning y análisis de contenido. Los resultados revelaron una prominente positividad y subjetividad en el campo léxico de cuatro cuentas en español y cuatro en inglés, con el reiterado empleo de los adjetivos feliz, nuevo, súper, etc. En suma, las cuentas infantiles expresan una tendencia de bucólica y festiva crianza.Instagram has become an integral part of the daily lives of children and young people, creating a kind of family album. In this context, we analyzed the polarity and subjectivity of 772 text posts in children’s accounts managed by parents on the platform through natural language processing with machine learning and content analysis. The results revealed a prominent positivity and subjectivity in the lexical field of four accounts in Spanish and four in English, with the repeated use of the adjectives happy, new, super, etc. In short, the children’s accounts express a tendency towards bucolic and festive upbringing

Human-Centered Technologies for Inclusive Collection and Analysis of Public-Generated Data

The meteoric rise in the popularity of public engagement platforms such as social media, customer review websites, and public input solicitation efforts strives for establishing an inclusive environment for the public to share their thoughts, ideas, opinions, and experiences. Many decisions made at a personal, local, or national scale are often fueled by data generated by the public. As such, inclusive collection, analysis, sensemaking, and utilization of pubic-generated data are crucial to support the exercise of successful decision-making processes. However, people often struggle to engage, participate, and share their opinions due to inaccessibility, the rigidity of traditional public engagement methods, and the lack of options to provide opinions while avoiding potential confrontations. Concurrently, data analysts and decision-makers grapple with the challenges of analyzing, sensemaking, and making informed decisions based on public-generated data, which includes high dimensionality, ambiguity present in human language, and a lack of tools and techniques catered to their needs. Novel technological interventions are therefore necessary to enable the public to share their input without barriers and allow decision-makers to capture, forage, peruse, and sublimate public-generated data into concrete and actionable insights. The goal of this dissertation is to demonstrate how human-centered approaches involve the stakeholders in the design, development, and evaluation of tools and techniques that can lead to inclusive, effective, and efficient approaches to public-generated data collection and analysis to support informed decision-making. To that end, in this dissertation, I first addressed the challenges of empowering the public to share their opinions by exploring two major opinion-sharing avenues --- social media and public consultation. To learn more about people\u27s social media experiences and challenges, I built two technology probes and conducted a qualitative exploratory study with 16 participants. This study is followed up by exploring the challenges of inclusive participation during public consultations such as town halls. Based on a formative study with 66 participants and 20 organizers, I designed and developed CommunityClick to enable reticent share their opinions silently and anonymously during town halls. Equipped with the knowledge and experiences from these works, I designed, developed, and evaluated technologies and methods to facilitate and accelerate informed data-driven decision-making based on increased public-generated data. Based on interviews with 14 analysts and decision-makers in the civic domain, I built a visual analytics system CommunityClick that can facilitate public input analysis by surfacing hidden insights, people\u27s reflections, and priorities. Leveraging the lessons learned during this work, I created a visual text analytics system that supports serendipitous discovery and balanced analysis of textual data to help make informed decisions. In this work, I contribute an understanding of how people collect and analyze public-generated data to fuel their decisions when they have increased exposure to alternative avenues for opinion-sharing. Through a series of human-centered studies, I highlight the challenges that inhibit inclusivity in opinion sharing and shortcomings of existing methods that prevent decision-makers to account for comprehensive public input that includes marginalized or unpopular opinions. To address these challenges, I designed, developed, and evaluated a collection of interactive systems including CommunityClick, CommunityPulse, and Serendyze. Through a rigorous set of evaluation strategies which include creativity sessions, controlled lab studies, in-the-wild deployment, and field experiments, I involved stakeholders to assess the effectiveness and utility of the built systems. Through the empirical evidence from these studies, I demonstrate how alternative designs for social media could enhance people\u27s social media experiences and enable them to make new connections with others to share opinions. In addition, I show how CommunityClick can be utilized to enable reticent attendees during public consultation to share their opinions while avoiding unwanted confrontation and allowing organizers to capture and account for silent feedback. I highlight how CommunityPulse allowed analysts and decision-makers to examine public input from multiple angles for an accelerated analysis and more informed decision-making. Furthermore, I demonstrate how supporting serendipitous discovery and balanced analysis using Serendyze can lead to more informed data-driven decision-making. I conclude the dissertation with a discussion on future avenues to expand this research including the facilitation of multi-user collaborative analysis, integration of multi-modal signals in the analysis of public-generated data, and potential adoption strategies for decision-support systems designed for inclusive collection and analysis of public-generated data

Sticks and Stones May Break My Bones but Words Will Never Hurt Me...Until I See Them: A Qualitative Content Analysis of Trolls in Relation to the Gricean Maxims and (IM)Polite Virtual Speech Acts

The troll is one of the most obtrusive and disruptive bad actors on the internet. Unlike other bad actors, the troll interacts on a more personal and intimate level with other internet users. Social media platforms, online communities, comment boards, and chatroom forums provide them with this opportunity. What distinguishes these social provocateurs from other bad actors are their virtual speech acts and online behaviors. These acts aim to incite anger, shame, or frustration in others through the weaponization of words, phrases, and other rhetoric. Online trolls come in all forms and use various speech tactics to insult and demean their target audiences. The goal of this research is to investigate trolls\u27 virtual speech acts and the impact of troll-like behaviors on online communities. Using Gricean maxims and politeness theory, this study seeks to identify common vernacular, word usage, and other language behaviors that trolls use to divert the conversation, insult others, and possibly affect fellow internet users’ mental health and well-being

Streaming to transgress: the racial politics of reactionary YouTubers and their audiences

This doctoral thesis examines the racial discourse of “alt-lite” YouTube personalities and their audiences. The term “alt-lite” was coined in the mid-2010s by self-avowed members of the white nationalist “alt-right” movement to castigate fellow reactionaries whose politics broadly aligned with theirs but who were not bold enough to explicitly embrace ethnonationalism. In this thesis, I examine “alt-lite” discourse as a calculated position within the attention economy, one that has been adopted with great success by popular reactionary influencers, particularly on YouTube. Understudied compared to other mainstream social media platforms, YouTube operates as an important launching pad for these right-wing micro-celebrities and serves as the primary field site for this qualitative study. Building on scholarship within critical race and digital studies, cultural studies, and political communication, this thesis asks: What discourses about race circulate within and around “alt-lite” YouTube channels? To answer this question, I draw on two and a half years of online data collection: over 250 YouTube videos; observation of nine Facebook, Reddit, and Discord groups; and semi-structured interviews with 18 current and former viewers of reactionary YouTube channels. I use qualitative content analysis and critical discourse analysis to interrogate these materials and draw conclusions about the strategies and impacts of “alt-lite” influencers. I find that these YouTubers traffic in white supremacist talking points, while adopting rhetorical strategies and legitimating practices that obfuscate their ideological extremity. Even as the most popular “alt-lite” YouTubers bring in substantial salaries from ad revenue, crowdsourcing, subscription fees, and partnerships, they are perceived by audiences as subversive “outsiders,” who are unbeholden to the institutional and ideological constraints of establishment media. Thus, “alt-lite” influencers are emblematic of an “alternative” right-wing media ecology that flourishes online, providing viewers with engaging political commentary that reflects their frustrations, keeps them entertained, and validates their desire to think for themselves

Expanding Data Imaginaries in Urban Planning:Foregrounding lived experience and community voices in studies of cities with participatory and digital visual methods

“Expanding Data Imaginaries in Urban Planning” synthesizes more than three years of industrial research conducted within Gehl and the Techno–Anthropology Lab at Aalborg University. Through practical experiments with social media images, digital photovoice, and participatory mapmaking, the project explores how visual materials created by citizens can be used within a digital and participatory methodology to reconfigure the empirical ground of data-driven urbanism. Drawing on a data feminist framework, the project uses visual research to elevate community voices and situate urban issues in lived experiences. As a Science and Technology Studies project, the PhD also utilizes its industrial position as an opportunity to study Gehl’s practices up close, unpacking collectively held narratives and visions that form a particular “data imaginary” and contribute to the production and perpetuation of the role of data in urban planning. The dissertation identifies seven epistemological commitments that shape the data imaginary at Gehl and act as discursive closures within their practice. To illustrate how planners might expand on these, the dissertation uses its own data experiments as speculative demonstrations of how to make alternative modes of knowing cities possible through participatory and digital visual methods

The Live Fashion Show in Mediatized Consumer Culture

This dissertation examines the fashion show and its mediatization as a microcosm of online medias impact on consumer culture. The contemporary fashion show is a brief, one-off live performance that presents a fashion house or brands upcoming seasonal collection to industrial insiders and invited clientele. The fashion show is the locus of communication between corporations and consumers and an arena in which commodities, personnel and industrial practices intersect. With the widespread mediatization of social life and the prevalence of digital media use in fashion in the past decade, critics mused that the live fashion show could become obsolete. Instead, its structure remains intact, and the entire circuit has mutated into an online spectacle, live streamed and proliferated in video, photographic and textual formats on multiple media platforms and applications. The fact that consumers can now see a collection at the moment of its debut marks a fundamental shift in fashion communication timeframes. Nonetheless, access to the fashion show remains limited to an elite cohort of fashion personnel, influencers and celebrities. This dissertation argues that the fashion show remains a focal event because it transmits the entire exclusive performance to an online spectatorship with an aim to build consumer desire to participate in fashion desire fulfilled in networked interactions and material purchases. I seek to here to problematize claims that the mediatization of the fashion show renders fashion democratic or accessible. To this end, I draw from performance and mediatization theories to illuminate that the fashion shows elite nature is predicated on a literal and social distinction between spectators temporal and spatial access. I perform qualitative close readings of fashion shows and transmitted footage and utilize content analysis and virtual and on-site participant observation to examine the class-based social relations that underpin and are re-asserted in mediatized fashion representations. This dissertation moreover situates the fashion show as a focal site via which to assess the social, industrial and material transformations that mediatization has effected in fashions economies

Investigating value propositions in social media: studies of brand and customer exchanges on Twitter

Social media presents one of the richest forums to investigate publicly explicit brand value propositions and its corresponding customer engagement. Seldom have researchers investigated the nature of value propositions available on social media and the insights that can be unearthed from available data. This work bridges this gap by studying the value propositions available on the Twitter platform. This thesis presents six different studies conducted to examine the nature of value propositions. The first study presents a value taxonomy comprising 15 value propositions that are identified in brand tweets. This taxonomy is tested for construct validity using a Delphi panel of 10 experts – 5 from information science and 5 from marketing. The second study demonstrates the utility of the taxonomy developed by identifying the 15 value propositions from brand tweets (nb=658) of the top-10 coffee brands using content analysis. The third study investigates the feedback provided by customers (nc=12077) for values propositioned by the top-10 coffee brands (for the 658 brand tweets). Also, it investigates which value propositions embedded in brand tweets attract ‘shallow’ vs. ‘deep’ engagement from customers. The fourth study is a replication of studies 2 and 3 for a different time-period. The data considered for studies 2 and 3 was for a 3-month period in 2015. In the fourth study, Twitter data for the same brands was analysed for a different (nb=290, nc=8811) 3-month period in 2018. This study thus examines the nature of change in value propositions across brands over time. The fifth study was on generalizability and replicates the investigation of brand and customer tweets (nb=635, nc=7035) in the market domain of the top-10 car brands in 2018. Lastly, study six conducted an evaluation of a software system called Value Analysis Toolkit (VAT) that was constructed based on the research findings in studies 1 - 5. This tool is targeted at researchers and practitioners who can use the tool to obtain value proposition-based insights from social media data (brand value propositions and the corresponding feedback from customers). The developed tool is evaluated for external validity using 35 students and 5 industry participants in three dimensions (tool’s analytics features, usability and usefulness). Overall, the contributions of this thesis are: a) a taxonomy to identify value propositions in Twitter (study 1) b) an approach to extract value proposition-based insights in brand tweets and the corresponding feedback from customers in the process of value co-creation (studies 2 - 5) for the top-10 coffee and car brands, and c) an operational tool (study 6) that can be used to analyse value propositions of various brands (e.g., compare value propositions of different brands), and identify which value propositions attract positive electronic word of mouth (eWOM). These value proposition-based insights can be used by social media managers to devise social-media strategies that are likely to stimulate positive discussions about a brand in social media

Facebook's Crowds and Publics: Law, Virality and the Regulation of Hate Speech Online in Contemporary India

A key feature of the material infrastructure of hate speech online on Facebook is virality – the rapid transmission of content over large distances through key nodes and actors on the platform. Virality is enabled by the bringing together of collectivities (crowds and publics) and connectivity provided by Facebook, which is accessed widely through Internet-enabled mobile phones. In contemporary India, increased connectivity provided by the material infrastructure of Facebook has reconfigured the relationship between crowds, publics and media, facilitated virality, and led to deadly illocutionary and perlocutionary effects such as inter-group violence and the subordination of minority groups. This thesis investigates how Facebook, through its content moderation policies and related institutional mechanisms and infrastructures, regulates the virality of hate speech online on the platform. Drawing on contemporary developments in India and the historical development of Indian hate speech doctrine, this thesis identifies emerging tensions between the global scale of hate speech regulation on Facebook and local context. These emerging tensions are visible in Facebook’s framing of its community standards on hate speech, and in the relationship between Facebook and national and subnational actors in India. These tensions are also visible in differences and contradictions in how actors who are part of Facebook’s governance model, including the Oversight Board, have approached the question of the regulation of hate speech online. This thesis employs mixed methods including a law-in-context reading of doctrine, documentary analysis and semi-structured interviews conducted with members of the Facebook Oversight Board, employees of Facebook and lawyers, academics and policy experts in the field. This thesis is part of a growing body of scholarship that examines the regulation of hate speech online and virality on Facebook through a non-United States and non-European lens