Fake news has great potential to cause damage to brand reputations and finances. Given the technical challenges of detecting fake news in time, it is inevitable that social media platforms will end up hosting fake news. The competition for attention and advertising revenue is intense. Many consumers read only the headlines. Fake news stories that mention brands in headlines can help news publishers garner social media engagement but can also hurt brands, raising concerns about brand protection. In this research, I focus on the first two stages of the information processing model – attending to information and encoding information (Berk 2018; Miller 1988).In Chapter 2, I investigate whether mentions of human and product brands are associated with news consumption and news retransmission (how brand mentions attract attention; the first stage of information processing). Using data from a news platform that generated both traditional and satirical (fake) news stories, I quantify the effects of brand mentions on social media engagement for both traditional and fake news. The analysis encompasses mentions of popular product brands, such as Apple, and mentions of human brands, such as famous politicians and actors. A framework based on uses and gratifications theory (UGT) aids in variable selection and the interpretation of results. My results imply that human brand mentions generally have a positive effect on news consumption and retransmission for both news formats, and product brand mentions affect engagement of satirical news via an interaction with news categories. Results provide further insights on the roles of sentiment, narrative style, and writing quality of news stories. The high potential of human and product brands in the headlines, especially human brands in satirical news, may be indicative of their potential to be misused by unscrupulous news media publishers. This reminds social media platforms of their responsibility to protect brands and consumers from fake news. Next, in Chapter 3, I examine the effectiveness of before-warnings (BWs) and after-warnings (AWs) in alerting consumers and reducing the persuasive influence of fake news on brand attitudes (how warning timing affects encoding; the second stage of information processing). Results reveal that for both negative and positive fake news, BWs are sometimes no more effective than no-warnings. Although BWs do encourage more critical processing of misinformation, this can distract consumers from the warning message. More importantly, Chapter 3 demonstrates a robust after-warning effect (AWE). Warning consumers after they have read fake news with AWs consistently leads to a higher reduction of persuasive influence (negative or positive) than BWs. AWs are more salient and arouse greater reactance to the false information than BWs. The resulting loss in control over how the news influenced attitudes and increased anger lead to the observed after-warning effect. News valence also matters since positive news is perceived to be more credible and processed less critically than negative news. AWs relative to BWs thus arouse feelings of being tricked when fake news is positive but not when it is negative, also leading to the after-warning effect. The findings have several theoretical and managerial implications. / Business Administration/Marketing

The scarce internet access in Ethiopia puts heavy weight on traditional media and people to spread news and information. By testing if the marketing strategy Word of Mouth is applicable on informative content, rather than just brands and products, this thesis explore the motivation to spread news as well as how it is received by a non-internet using group. As with brands, a common trigger for WOM was the subject being brought up in a discussion, both offline and online. Conditions that increased WOM in marketing such as being sociable and feeling a responsibility also increased WOM for more political content. The study also found that there is a low trust for internet as a source, but a high trust for the word of many. If the message was heard multiple times it was more believable, even though a primary source was lacking. In general both internet users and non-internet users were actively spreading information with the reason that it needed to be spread, something that was concluded as a collectivist action where information is spread quickly through social ties. Non-internet users were considered to be extra fragile and exposed to fake news due to the unequal distribution of information and technology. Since trust was based on the message of many, echo chambers and confirmation bias is discussed, as well as how Ethiopia might tackle the segregation of technology in the country in order to decrease inequality in the future. / Den svaga tillgången till internetuppkoppling i Etiopien lägger ett stort ansvar på traditionell media, och människor, för att sprida nyheter och information till landets stora befolkning. Genom att testa om marknadsföringsstrategin Word of Mouth också är applicerbar på informativa budskap undersöker denna uppsats motivationen bakom att sprida nyheter, samt hur denna mottas av en grupp som inte använder internet. Liksom med varumärken var en vanlig trigger för WOM med informativ kontext att ämnet nämndes i en pågående diskussion, både online och offline. Förutsättningar som stärkte WOM vid marknadsföring, såsom att vara social och känna ett samhällsansvar ökade också WOM för nyheter. Studien fann också att det var låg tillit för internet som källa, men att det fanns stor tilltro till information som upprepades av olika personer. Ett budskap som hördes från flera olika var mer trovärdigt, oavsett vilken den primära källan var eller om den saknades helt. Generellt spred både internetanvändare och icke-användarna information av anledningen att det behövdes spridas och höras av alla invånare, vilket tolkades som en kollektivistisk handling där nyheter snabbt spreds i sociala nätverk. De som inte använder internet ansågs vara extra exponerade för fake news på grund av den ojämställda distributionen av information och tillgången till teknologi. Då tillit var baserat på upprepning från många diskuterar uppsatsen även echo chambers och confirmation bias, samt hur Etiopien i framtiden kan tackla den tekniska segregationen.

På senare år har dokumentärfilmsgenren hamnat i skottlinjen för en kritik som riktar sig mot sanningsrelativism och falska nyheter. Den här uppsatsen undersöker hur svenska dokumentärfilmare förhåller sig till de krav på äkthet och transparens som förväntas av dem, och i vilken mån dessa krav avspeglar sig i filmarnas arbete. Intervjuer med fyra svenska dokumentärfilmare ligger till grund för uppsatsen och frågorna som ställts står i direkt koppling till den debatt som florerat de senaste åren kring huruvida dokumentära berättelser i likhet med journalistik och nyheter riskerar att bli sanningsrelativa. Forskning visar på ett samband mellan dagens medieklimat och urvattnandet av sanningsbegreppet genom framväxten av exempelvis trollsidor och ”fake news”, vilket delvis också förändrat samtalet om sant och falskt på den dokumentära arenan. Resultatet av undersökningen visar att filmarna tagit intryck av den förändrade diskurs som på senare år växt fram kring dokumentärfilmens autenticitetskrav, men att detta inte förändrat deras sätt att närma sig sitt material och hur de ser på sin yrkesroll. Däremot finns en stor medvetenhet kring vikten av en öppen dialog, transparens kring den kreativa processen och värdet i en informerad publik.

No description available.

China is accused of conducting disinformation campaigns on Taiwan's social media. Existing studies on foreign interventions in democratic societies predict that such disinformation campaigns should lead to increasing partisan polarization within Taiwan. We argue that a backlash effect, making Taiwan's citizens more united against China, is equally plausible. We conduct a survey experiment exposing participants to a real-life rumour and rebuttal to test these competing hypotheses. We find, at best, mixed evidence for polarization. Although neither rumour nor rebuttal mention China, there is consistent evidence of backlash against China. Most notably, participants across the political spectrum are more inclined to support Taiwanese independence after viewing the rumour rebuttal. These findings indicate that citizens may put aside partisanship when confronted with false news that is plausibly linked to an external actor. We conclude by discussing the broader applicability of our theory and implications for cross-Strait relations.

The great advance of communication technology comes with a rapid increase of disinformation in many kinds and shapes; manipulated images are one of the primary examples of disinformation that can affect many users. Such activity can severely impact public behavior, attitude, and belief or sway the viewers' perception in any malicious or benign direction. Additionally, adversarial attacks targeting deep learning models pose a severe risk to computer vision applications. This dissertation explores ways of detecting and resisting manipulated or adversarial attack images. The first contribution evaluates perceptual hashing (pHash) algorithms for detecting image manipulation on social media platforms like Facebook and Twitter. The study demonstrates the differences in image processing between the two platforms and proposes a new approach to find the optimal detection threshold for each algorithm. The next contribution develops a new pHash authentication to detect fake imagery on social media networks, using a self-supervised learning framework and contrastive loss. In addition, a fake image sample generator is developed to cover three major image manipulating operations (copy-move, splicing, removal). The proposed authentication technique outperforms the state-of-the-art pHash methods. The third contribution addresses the challenges of adversarial attacks to deep learning models. A new adversarial-aware deep learning system is proposed using a classical machine learning model as the secondary verification system to complement the primary deep learning model in image classification. The proposed approach outperforms current state-of-the-art adversarial defense systems. Finally, the fourth contribution fuses big data from Extra-Military resources to support military decision-making. The study proposes a workflow, reviews data availability, security, privacy, and integrity challenges, and suggests solutions. A demonstration of the proposed image authentication is introduced to prevent wrong decisions and increase integrity. Overall, the dissertation provides practical solutions for detecting manipulated and adversarial attack images and integrates our proposed solutions in supporting military decision-making workflow.

No description available.

Studien belyser dagens spridning av falsk information på sociala medier och vad som händer när sådan information dementeras av användare på sociala medier. Denna uppsats är en fallstudie och undersöker vad reaktionerna blir från Facebook-användare när en publicerings osanning belyses i kommentarsfältet. En netnografisk metod har tillämpats för att samla in data. Kommentarer vid tre olika fall där falska publiceringar har spridits har undersökts. Kommentarer har samlats in från det sociala nätverket Facebook för analys. Studien konkluderar att kommentarer som belyser falsk information genererar en förhållandevis liten mängd interaktion. Samtidigt får dessa kommentarer i högre grad positiv respons än negativ. / This essay highlights the current distribution of false information on social media and what happens when users on social media dismisses such information. This essay is a case study and investigates what the reactions are from Facebook users when a published falsehood is highlighted in the comment section. A netnographic method has been used to collect data. Comments on three different cases where false information have been spread have been investigated. Comments have been collected from online social community Facebook for analysis. The study concludes that comments that highlight false information generate a relatively small amount of interaction. At the same time, these comments are more often positive than negative.

In the past decade, a fundamental research topic in the information systems (IS) discipline has been to examine the value of online platforms on businesses, society, and consumers, notably in the form of improved efficiency in information sharing, consumer engagement, and increased sales. However, the risks rooted in online platforms may cannibalize the value created, which have received limited attention in the literature and practice. In my dissertation, I attempt to fill this gap in the literature by providing a comprehensive analysis of the risks of online platforms from the angle of these three main entities in the ecosystem with three separate yet related essays. The first essay focuses on the risks for businesses that leverage social media platforms, and assesses how their posting on social media fan pages affects consumers’ decision to purchase and unfollow from the firms. The second essay focuses on the risks of fake news on social media and how social media platforms may use identity verification to reduce online anonymity and combat this increasingly critical social problem. The third essay focuses on estimating the risks of using monetary incentives to motivate consumers to write online product reviews, and examines how such strategy may affect product sales. Our studies have theoretical and practical implications for designing effective online platform information systems. / Business Administration/Management Information Systems

Yes / Deepfakes constitute fake content -generally in the form of video clips and other media formats such as images or audio- created using deep learning algorithms. With the rapid development of artificial intelligence (AI) technologies, the deepfake content is becoming more sophisticated, with the developed detection techniques proving to be less effective. So far, most of the detection techniques in the literature are based on AI algorithms and can be considered as passive. This paper presents a proof-of-concept deepfake detection system that detects fake news video clips generated using voice impersonation. In the proposed scheme, digital watermarks are embedded in the audio track of a video using a hybrid speech watermarking technique. This is an active approach for deepfake detection. A standalone software application can perform the detection of robust and fragile watermarks. Simulations are performed to evaluate the embedded watermark's robustness against common signal processing and video integrity attacks. As far as we know, this is one of the first few attempts to use digital watermarking for fake content detection. / EIG CONCERT-Japan call to the project entitled “Detection of fake newS on SocIal MedIa pLAtfoRms” (DISSIMILAR) through grants PCI2020-120689-2 (Ministry of Science and Innovation, Spain) and JPMJSC20C3 (JST SICORP, Japan). In addition, the work of the first two authors was partly funded by the Spanish Government through RTI2018-095094-B-C22 “CONSENT”