1,786 research outputs found
The lexicocalorimeter: Gauging public health through caloric input and output on social media
We propose and develop a Lexicocalorimeter: an online, interactive instrument for measuring the caloric content of social media and other large-scale texts. We do so by constructing extensive yet improvable tables of food and activity related phrases, and respectively assigning them with sourced estimates of caloric intake and expenditure. We show that for Twitter, our naive measures of caloric input , caloric output , and the ratio of these measures are all strong correlates with health and well-being measures for the contiguous United States. Our caloric balance measure in many cases outperforms both its constituent quantities; is tunable to specific health and well-being measures such as diabetes rates; has the capability of providing a real-time signal reflecting a population\u27s health; and has the potential to be used alongside traditional survey data in the development of public policy and collective self-awareness. Because our Lexicocalorimeter is a linear superposition of principled phrase scores, we also show we can move beyond correlations to explore what people talk about in collective detail, and assist in the understanding and explanation of how population-scale conditions vary, a capacity unavailable to black-box type methods
Measuring Social Influence in Online Social Networks - Focus on Human Behavior Analytics
With the advent of online social networks (OSN) and their ever-expanding reach, researchers seek to determine a social media userâs social influence (SI) proficiency. Despite its exploding application across multiple domains, the research confronts unprecedented practical challenges due to a lack of systematic examination of human behavior characteristics that impart social influence. This work aims to give a methodical overview by conducting a targeted literature analysis to appraise the accuracy and usefulness of past publications. The finding suggests that first, it is necessary to incorporate behavior analytics into statistical measurement models. Second, there is a severe imbalance between the abundance of theoretical research and the scarcity of empirical work to underpin the collective psychological theories to macro-level predictions. Thirdly, it is crucial to incorporate human sentiments and emotions into any measure of SI, particularly as OSN has endowed everyone with the intrinsic ability to influence others. The paper also suggests the merits of three primary research horizons for future considerations
Marketing Communications: How Strategic Advertising Enhances Good Customer Relations and Assures Brand Loyalty â The Case of Celtel, Tanzania
This study investigates how marketing communications in strategic advertising scientifically brings long-term profits to a company in regard to management of customer relations and brand loyalty. Advertising being a function of attention, perception and trial brings about brand expectation to customers. Customers compare brand performance to their pr-existing expectations to judge and position themselves from brandâs perspective. Using a Tobinâs âqâ concept, the authors analyze the advertising strategy of Celtel, Tanzania and study how it is used to manage customer relations and project repurchase behavior for Celtel services. A comparative study of Celtel Customers and non-Celtel customers is done. Empirical results show that Celtel customers are more loyal to Celtel brands and Celtel advertising strategies encourage higher brand loyalty. Further, an analysis of the customer confidence for repurchase behavior projection using similar measures shows a higher value with Celtel Customers database than Non-Celtel Customers database
Transforming teacher education, an activity theory analysis
This paper explores the work of teacher education in England and Scotland. It seeks to locate this work within conflicting socio-cultural views of professional practice and academic work. Drawing on an activity theory framework that integrates the analysis of these contradictory discourses with a study of teacher educatorsâ practical activities, including the material artefacts that mediate the work, the paper offers a critical perspective on the social organisation of university-based teacher education. Informed by Engeströmâs activity theory concept of transformation, the paper extends the discussion of contradictions in teacher education to consider the wider socio-cultural relations of the work. The findings raise important questions about the way in which teacher education work within universities is organised and the division of labour between schools and universities
Social media mining under the COVID-19 context: Progress, challenges, and opportunities
Social media platforms allow users worldwide to create and share information, forging vast sensing networks that
allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the
COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges
from various perspectives. This review summarizes the progress of social media data mining studies in the
COVID-19 contexts and categorizes them into six major domains, including early warning and detection, human
mobility monitoring, communication and information conveying, public attitudes and emotions, infodemic and
misinformation, and hatred and violence. We further document essential features of publicly available COVID-19
related social media data archives that will benefit research communities in conducting replicable and reproïżœducible studies. In addition, we discuss seven challenges in social media analytics associated with their potential
impacts on derived COVID-19 findings, followed by our visions for the possible paths forward in regard to social
media-based COVID-19 investigations. This review serves as a valuable reference that recaps social media mining
efforts in COVID-19 related studies and provides future directions along which the information harnessed from
social media can be used to address public health emergencies
Recipe popularity prediction in Finnish social media by machine learning models
Abstract. In recent times, the internet has emerged as a primary source of cooking inspiration, eating experiences and food social gathering with a majority of individuals turning to online recipes, surpassing the usage of traditional cookbooks. However, there is a growing concern about the healthiness of online recipes. This thesis focuses on unraveling the determinants of online recipe popularity by analyzing a dataset comprising more than 5000 recipes from Valio, one of Finlandâs leading corporations. Valioâs website serves as a representation of diverse cooking preferences among users in Finland. Through examination of recipe attributes such as nutritional content (energy, fat, salt, etc.), food preparation complexity (cooking time, number of steps, required ingredients, etc.), and user engagement (the number of comments, ratings, sentiment of comments, etc.), we aim to pinpoint the critical elements influencing the popularity of online recipes. Our predictive model-Logistic Regression (classification accuracy and F1 score are 0.93 and 0.9 respectively)- substantiates the existence of pertinent recipe characteristics that significantly influence their rates. The dataset we employ is notably influenced by user engagement features, particularly the number of received ratings and comments. In other words, recipes that garner more attention in terms of comments and ratings tend to have higher rates values (i.e., more popular). Additionally, our findings reveal that a substantial portion of Valioâs recipes falls within the medium health Food Standards Agency (FSA) score range, and intriguingly, recipes deemed less healthy tend to receive higher average ratings from users. This study advances our comprehension of the factors contributing to the popularity of online recipes, providing valuable insights into contemporary cooking preferences in Finland as well as guiding future dietary policy shift.Reseptin suosion ennustaminen suomalaisessa sosiaalisessa mediassa koneoppimismalleilla. TiivistelmĂ€. Internet on viime aikoina noussut ensisijaiseksi inspiraation lĂ€hteeksi ruoanlaitossa, ja suurin osa ihmisistĂ€ on siirtynyt kĂ€yttĂ€mÀÀn verkkoreseptejĂ€ perinteisten keittokirjojen sijaan. Huoli verkkoreseptien terveellisyydestĂ€ on kuitenkin kasvava. TĂ€mĂ€ opinnĂ€ytetyö keskittyy verkkoreseptien suosioon vaikuttavien tekijöiden selvittĂ€miseen analysoimalla yli 5000 reseptistĂ€ koostuvaa aineistoa Suomen johtavalta maitotuoteyritykseltĂ€, Valiolta. Valion verkkosivujen reseptit edustavat monipuolisesti suomalaisten kĂ€yttĂ€jien ruoanlaittotottumuksia. Tarkastelemalla reseptin ominaisuuksia, kuten ravintoarvoa (energia, rasva, suola, jne.), valmistuksen monimutkaisuutta (keittoaika, vaiheiden mÀÀrĂ€, tarvittavat ainesosat, jne.) ja kĂ€yttĂ€jien sitoutumista (kommenttien mÀÀrĂ€, arviot, kommenttien mieliala, jne.), pyrimme paikantamaan kriittiset tekijĂ€t, jotka vaikuttavat verkkoreseptien suosioon. Ennustava mallimme â Logistic Regression (luokituksen tarkkuus 0,93 ja F1-pisteet 0,9 ) â osoitti merkitsevien reseptiominaisuuksien olemassaolon. Ne vaikuttivat merkittĂ€vĂ€sti reseptien suosioon. KĂ€yttĂ€miimme tietojoukkoihin vaikuttivat merkittĂ€vĂ€sti kĂ€yttĂ€jien sitoutumisominaisuudet, erityisesti vastaanotettujen arvioiden ja kommenttien mÀÀrĂ€. Toisin sanoen reseptit, jotka saivat enemmĂ€n huomiota kommenteissa ja arvioissa, olivat yleensĂ€ suositumpia. LisĂ€ksi selvisi, ettĂ€ huomattava osa Valion resepteistĂ€ kuuluu keskitason terveyspisteiden alueelle (arvioituna FSA Scorella), ja mielenkiintoisesti, vĂ€hemmĂ€n terveellisiksi katsotut reseptit saavat kĂ€yttĂ€jiltĂ€ yleensĂ€ korkeamman keskiarvon. TĂ€mĂ€ tutkimus edistÀÀ ymmĂ€rrystĂ€mme verkkoreseptien suosioon vaikuttavista tekijöistĂ€ ja tarjoaa arvokasta nĂ€kemystĂ€ nykypĂ€ivĂ€n ruoanlaittotottumuksista Suomessa
Trusted Autonomy and Cognitive Cyber Symbiosis: Open Challenges
This paper considers two emerging interdisciplinary, but related topics that are likely to create tipping points in advancing the engineering and science areas. Trusted Autonomy (TA) is a field of research that focuses on understanding and designing the interaction space between two entities each of which exhibits a level of autonomy. These entities can be humans, machines, or a mix of the two. Cognitive Cyber Symbiosis (CoCyS) is a cloud that uses humans and machines for decision-making. In CoCyS, humanâmachine teams are viewed as a network with each node comprising humans (as computational machines) or computers. CoCyS focuses on the architecture and interface of a Trusted Autonomous System. This paper examines these two concepts and seeks to remove ambiguity by introducing formal definitions for these concepts. It then discusses open challenges for TA and CoCyS, that is, whether a team made of humans and machines can work in fluid, seamless harmony
The Heart's Content: Media and Marketing after the Attention Economy
Capturing user attention and selling it to advertisers has long served as the basic economic model for online media. In this thesis, I investigate these companiesâ growing desire to go deeperâto plumb their usersâ hearts and minds, to transform their emotions into quantifiable data, and to sell those feelings to marketers. To shed light on the recent history of this trend, I take up the website Upworthy as a key case study in online publishersâ efforts to negotiate an attention economy in flux. By analyzing the evolving methods Upworthy used to capture, measure, and sell reader attention to clients, I trace their audience engagement and revenue generation strategies along a trajectory from attention to emotion to empathy. As the attention economy becomes more complex, the perceived need to monitor and measure the psychological, emotional, and affective dimensions of user engagement grows. Biometric emotion-detection technology provides a means to examine the ramifications of these proliferating forms of psychological surveillance and datafication, including their potential to reinforce hegemonic emotional norms. Finally, with the possibility of what I call the âempathy economyâ on the horizon, I consider empathyâs political implications, the intimate data and sensitive technology that such an economy would require, and the forms of emotional commodification, standardization, and optimization it could engender
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