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Investor sentiment from images: a few-shot learning investigation
Get PDFPurpose: This research aims to extract emotional features from New York Times news images (2018–2023) using few-shot learning approaches. Leveraging machine learning, it offers a systematic investigation into how image-driven emotions affect investor behavior in the US equity market and contribute to the prediction of market movements.
Design/methodology/approach: This study employs the DeepEMD model to extract emotional features from 181,233 news images, constructing a daily sentiment index based on visual media. By defining sentiment thresholds, the study develops differentiated strategies for positive and negative emotional signals. In addition, it integrates four machine learning models – AdaBoost, Support Vector Machine, ExtraTrees and Random Forest – alongside a traditional linear regression model to forecast the prices of various US stock market indices.
Findings: This study finds that news image sentiment has a significant impact on financial markets. Positive sentiment strategies applied to serious news topics are associated with higher returns, whereas negative sentiment in entertainment-related content signals potential opportunities for contrarian investment. Moreover, the influence of image-based sentiment on the market exhibits a delayed effect of approximately 2–3 days, with particularly strong predictive power for small-cap stocks. Compared with the traditional linear models, machine learning approaches demonstrate superior performance in capturing the nonlinear dynamics between sentiment and market behavior, offering novel analytical tools for behavioral finance research and sentiment-driven anomaly-based investment strategies.
Originality/value: This study integrates visual data analysis into the domain of behavioral finance, highlighting the distinctive role of image-based sentiment in uncovering market anomalies and informing investment strategies
Navigating ethical tensions in social enterprises: a business ethics as practice perspective
No full textSocial enterprises must achieve both social and financial goals. These goals need to be aligned when balancing divergent interests for positive social change, financial viability and securing suitable funding. Tensions between the goals can frequently arise. To date, the literature has paid little attention to identifying and classifying ethical tensions that social entrepreneurs face in practice. We develop a conceptual framework for addressing ethical tensions informed by two key sources. Using normative ethical theory as our reference framework, we draw on insights from a series of interviews and practice‐led observations with entrepreneurs and leaders of social enterprises to support our theorising. We identify a triangle of interrelated ethical tensions related to organising, belonging and conjoint learning and performing. By integrating traditional ethical theories with a business ethics‐as‐practice perspective, our findings suggest that navigating ethical tensions in social enterprises, requires an agile approach to ethical decision‐making, marked by ethical vitality in using various ethical approaches, in context‐specific and evolving ways. We suggest a series of propositions that future empirical research might examine
Demand flexibility and price elasticity: an analysis of the intra-day price elasticity of demand
No full textEnergy demand flexibility is widely considered a key part of the net-zero ambitions. However, many questions remain in regard to both the amount of flexibility available, and the most effective ways to harness said flexibility. Price-based incentives have been the go-to solution thus far for attempting to harness demand flexibility; the underlying assumption being that the price is the main factor at play when it comes to deciding whether or not to consume energy. In practice, however, what is observed is a large variability in price elasticity, or the responsiveness to time-varying energy rates. This variability depends on factors such as the on-peak to off-peak price ratios, uptake of technologies, and the wider context. It is observed not only across the consumer base but also throughout the day, as energy demand patterns are directly linked to broader activity patterns that dictate both the timing and intensity of energy demand. Understanding this intra-day variability in price elasticity is key to developing more effective demand flexibility interventions. However, to date, research investigating intra-day price elasticity remains limited. In this paper we present the preliminary results of the process of adapting an econometric model, originally developed to link energy wholesale prices to demand patterns, to a more targeted study of the intra-day price elasticity based on retail prices; that is, the prices actually experienced by end-users. The primary advantage of this model is that it provides a simple and straightforward way of assessing the extent to which price elasticity exhibits variation throughout the day. Moreover, the method proposed here can just as easily be applied to any other appropriate data set containing both fixed electricity tariffs - which do not vary based on the time of the day- as well as spot prices - where hourly rates change hourly. The analysis presented in this paper is carried out on a dataset collected as part of a Norwegian study from 2023 to understand households’ responses to the changes in energy prices experienced during the recent energy crisis experienced in Europe. Unpacking the intra-day variability of the price elasticity of energy demand is critical, as the extent to which households are either able or willing to respond to price signals is heavily influenced by the time of day and broader daily routines. Therefore, it is important to understand whether the periods where households are more prone to respond to such stimuli overlap with the periods where flexibility interventions are needed the most. Effective policy-making relies on this kind of information. Placing consumers’ demand patterns at the centre of policy-making debates increases the likelihood of implementing policies that are both effective and widely accepted. The paper concludes that intra-day price elasticity is key to developing demand flexibility interventions which reflect the timing of people’s activities
Innovations and challenges in digital literacies: literacies of repair
No full textInnovations and Challenges in Digital Literacies questions whether the current theoretical frameworks and pedagogical practices around digital literacies are sufficient to confront the technological, social, and political crises around digital media that we are experiencing today.
Drawing on extensive research in digital literacies, discourse analysis, and sociotechnical systems, Jones reimagines digital literacies not simply as skills for making meaning and navigating information but as a more holistic project of figuring out how to ‘fix’ what is ‘broken’ about the internet and our broader societies. The book focuses on seven key ‘sites of repair’—action, attention, affect, affinity, visibility, truth, and humanity—each site offering insights into how agency, emotions, relationships, knowledge, and ‘intelligence’ emerge through our entanglements with digital technologies. The text aims to provoke debate about how we define digital literacies in an age of political polarisation and rapid technological change. It provides powerful tools for teaching, learning, and living more ethically with digital media.
With this book, Jones invites readers to see themselves not just as users of digital technology, but as fixers of broken systems—and caretakers of our increasingly fragile world. This approach provides a framework for educators, students, and researchers to collaboratively develop practical strategies to challenge the logics of technological and social systems, cultivating new literacies for an age of online misinformation, algorithmic governance, and generative AI
Improvement of fog forecasting using atmospheric electricity
No full textSince atmospheric electricity was first studied, fog has been known to affect measurements of it. In the 1900s, some researchers attempted to show that measurements of
the potential gradient (PG) could be used in order to predict fog, but with inconclusive
results. In this thesis, the interactions between fog and atmospheric electricity are
studied from three different approaches.
First, a method of detecting the start time of fog events from visibility is proposed,
which is then used to analyse 47 fog events in Reading. The PG increases in fog by a
median of 57.6 V/m compared to pre-fog values. Although the PG does not always
increase before the fog events begin, it does begin increasing more than two hours in
advance of the fog about twice as often as visibility measurements start changing to
the same degree.
Secondly, droplet size distribution measurements are used alongside physical
theory to evaluate the cause of the changes in the PG. By calculating the expected
effect on PG using polydisperse fog droplet measurements as input to a model, it
is found that fog droplets explain many of the variations in PG in fog (correlations
up to 0.6, and a p-value of down to 0.003) but that other effects are also relevant. A
simulation of fog development showed the PG predicting fog 10 minutes earlier than
the visibility.
Finally, profiles of the vertical space charge in fog are measured on a tethered
balloon platform, finding charges of up to ±100 nCm−3 during fog, which was more
than expected from past modelling. These highly charged regions in fog could
produce changes in the PG.
In conclusion, the variations in PG, when used alongside visibility and humidity,
show many signs of being an excellent tool to be used in the prediction of fog
‘Am I multilingual?’ The relationship between pre-service teachers’ multilingual identities, language experiences and beliefs about multilingualism
Get PDFDespite an increase in research on language learners’ multilingual identities (MId), the construct of teacher multilingual identities as a gateway to linguistically inclusive teaching remains under-researched, and the factors shaping teachers’ willingness to claim and express a multilingual identity remain unclear. This article explores two factors that might influence teachers’ MId, namely teachers’ language experience and beliefs about multilingualism. MId data was obtained through a questionnaire administered to 117 pre-service teachers spanning subject specialism in England. A sub-sample of 51 participants also completed a Q-sorting activity where they expressed their views of multilingualism. Correlation analyses revealed that perceived language fluency had the strongest association with MId. Furthermore, those participants who held a prescriptive view of languages and perceived multilingualism as the exception in schools also tended to express a monolingual identity. The article concludes with a discussion of the implications of the study findings for researchers and teacher educators
Does differential habitat selection facilitate coexistence between badgers and hedgehogs?
Get PDFPredicting the spatial and temporal responses of species exhibiting intraguild predation (IGP) relationships is difficult due to variation in potential interactions and environmental context. Eurasian badgers (Meles meles) are intraguild predators of European hedgehogs (Erinaceus europaeus) and are implicated in their population decline via both direct predation and competition for shared food resources. Previous studies have shown spatial separation between these species and attributed this to hedgehogs experiencing a ‘landscape of fear’, but little is known about the potential role of differential habitat use. We estimated the density and occupancy of both species at 22 rural study sites in England and Wales, to explore whether food availability, habitat or the presence of badgers, explained hedgehog distributions. Hedgehog density varied significantly across major rural land uses, whereas badger density did not. Although both species coexisted at a regional (1 km2) scale, occupancy modelling showed spatial segregation at a finer (individual camera trap) scale, associated with differential habitat use. In contrast to badgers, hedgehogs were recorded near buildings, and in areas supporting lower invertebrate biomass. This is in agreement with IGP theory, whereby IG‐prey may occupy suboptimal habitat to avoid predation; however, hedgehog habitat use did not vary relative to the presence of badgers. Badger and hedgehog temporal activity showed no evidence of separation. Although these findings are consistent with hedgehogs avoiding badgers via a landscape of fear, they are also indicative of differential habitat use, highlighting the need for more holistic studies considering variation in habitat selection and food availability when investigating intraguild relationships. Future studies exploring alternative hypotheses for urban habitat selection by hedgehogs are needed to better understand how possible spatial niche partitioning may support their coexistence with badgers in some areas
Coastlines need natural defences
No full textThe UK’s coastline is under increasing threat. Rising sea levels coupled with more frequent and powerful storms caused by climate change are putting communities, businesses, and wildlife at risk of flooding and erosion.
For decades, we’ve relied on hard defences like seawalls and groynes to protect us. These structures are familiar and often effective, but they come with downsides – they can be expensive, need regular maintenance, and sometimes cause more harm than good by shifting erosion problems to neighbouring coastal areas.
An alternative way of thinking is now gaining attention
