Alternative Labeling Research Articles

A Machine Learning Approach for Sentiment Analysis Using Social Media Posts

Sentiment analysis on Twitter provides organizations and persons with quick and effective instrument to observe the public's perceptions of them and their competition. A modest number of assessment datasets have been produced in recent years to check the efficiency of sentiment analysis algorithms on Twitter. Researchers offer a review of eight publicly accessible as well as manually annotated assessment datasets for analyzing Twitter sentiment in this research. As a result of this evaluation, we demonstrate that is a widespread weakness of many when using these datasets performing at sentiment analysis the objective (entity) level is indeed the absence of different sentiment classifications across tweets as well as the objects contained in them.[1], As an example all of that "I love my iPhone but I despise my iPad." Could be marked with a made-by-mixing classify however the object iPhone contained within this Twitter post should be annotated with just a label with an optimism. To get around this restriction and enhance existing assessment We have datasets that provide STS-Gold a novel assessment of datasets in which tweets or objects (entities) remain tagged separately hence might show alternative opinion labels. Though research furthermore compares the various datasets on multiple characteristics such as an entire quantity of posts as well as vocabulary size and sparsity.[2] In addition, look at pair by pair relationships between these variables and how they relate to sentiment classifier performance on various data. In this study we used five different classifiers and compared them and, in our experiment, we found that the bagging ensemble classifier performed best among them and have an accuracy level of 94.2% for the GASP dataset and 91.3% for the STS-Gold dataset.

Speaker Demographics Modulate Listeners' Neural Correlates of Spoken Word Processing.

In language comprehension, listeners expect a speaker to be consistent in their word choice for labeling the same object. For instance, if a speaker previously refers to a piece of furniture as a "couch," in subsequent references, listeners would expect the speaker to repeat this label instead of switching to an alternative label such as "sofa." Moreover, it has been found that speakers' demographic backgrounds, often inferred from their voice, influence how listeners process their language. The question in focus, therefore, is whether speaker demographics influence how listeners expect the speaker to repeat or switch labels. In this study, we used ERPs to investigate whether listeners expect a child speaker to be less likely to switch labels compared to an adult speaker, given the common belief that children are less flexible in language use. In the experiment, we used 80 pictures with alternative labels in Mandarin Chinese (e.g., yi1sheng1 vs. dai4fu, "doctor"). Each picture was presented twice over two experimental phases: In the establishment phase, participants listened to an adult or a child naming a picture with one of the labels and decided whether the label matched the picture they saw; in the test phase, participants listened to the same speaker naming the same picture by either repeating the original label or switching to an alternative label and, again, decided whether the label matched the picture they saw. ERP results in the test phase revealed that, compared to repeated labels, switched labels elicited an N400 effect (300-600 msec after label onset) and a P600 effect (600-1000 msec after label onset). Critically, the N400 effect was larger when listeners were exposed to the child speaker than to the adult speaker, suggesting that listeners found a switched label harder to comprehend when it was produced by a child speaker than an adult speaker. Our study shows that the perceived speaker demographic backgrounds influence listeners' neural responses to spoken words, particularly in relation to their expectations regarding the speaker's label switching behavior. This finding contributes to a broader understanding of the relationship between social cognition and language processing.

When is prostate cancer really cancer?

Prostate cancer (PC) is a major cause of cancer-related deaths worldwide, with far more diagnoses than deaths annually. Recent discussions have challenged whether Grade Group 1 (GG1) PC should be labeled "cancer" due to its indolent nature. To address this question, an international symposium convened stakeholders from various fields. We summarize key discussion points: autopsy studies reveal GG1 is so common in aging males as to be perhaps a normal aspect of aging. Pure GG1 has no capacity to metastasize. Modern diagnostic pathways focus on detecting higher-grade disease, explicitly omitting biopsy if GG 2 or higher is not suspected, so GG1 has effectively become an "incidentaloma." Recent spatial transcriptomics of prostate sections identifies a continuum of genomic changes-including alterations characteristic of malignancy in histologically normal regions, so the designation of cancer based entirely on conventional pathology findings increasingly seems arbitrary at least to an extent. Pathologists discussed heterogeneity and diagnostic challenges, suggesting "acinar neoplasm" as one possible alternative label. GG1 should not be considered "normal," and absolutely requires ongoing active surveillance; whether patients would adhere to surveillance absent a cancer diagnosis is unknown. Patient perspectives highlighted the adverse effects of overtreatment and the burden of a cancer diagnosis. The anticipated impact on screening and treatment varies across health-care systems, but many believe public health would on balance greatly improve if GG1-along with lesions in other organs with no capacity to cause symptoms or threaten life-were labeled something other than "cancer." Ultimately, our goal is to reduce PC mortality while minimizing harms associated with both overdiagnosis and overtreatment.

Neuropsychological performance labels: do patients understand?

Objective: Descriptive labels to communicate performance are integral in neuropsychological reports. Although the American Academy of Clinical Neuropsychology (AACN) reached consensus on standardizing uniform labels of performance, consumer understanding of these labels is unclear. This pilot prospective cohort study evaluated patient, family member, and medical provider understanding of neuropsychological performance labels. Method: Patients (n = 62), family members (n = 31), and referral sources (n = 34) completed a 13-question survey evaluating the uniform label system and an alternative, patient-centered language system (PCL). Questions assessed label knowledge and associated percentiles and relative relationships between labels. Results: Patients had significantly higher accuracy on knowledge questions using PCL labels (54.8%) versus AACN labels (32.2%) as were families (51.6% versus 35.5%). When ranking labels, providers and patients were more accurate when using PCL labels compared to AACN labels, although no significant difference was seen in the family group. Generally, participants were more accurate in identifying highest/lowest scores using AACN labels and more accurate in identifying relatively higher and lower scores using PCL terminology. Conclusions: Results illustrate that current and alternative score labels may not be understandable for audiences who read and base decisions on neuropsychological reports. The findings highlight the need for further consideration of patient-centered language to improve understanding of neuropsychological score labels.

Quo vadis DSM-6? An expert survey on the classification, diagnosis, and differential diagnosis of body-focused repetitive behaviors

BackgroundMany conditions we now call body-focused repetitive behaviors (BFRBs) have been subject to research for several decades, most notably trichotillomania and skin picking. However, the American Psychiatric Association did not combine these conditions into a single category, body-focused repetitive behavior disorder (BFRBD), until the fifth edition of the DSM (2013). Several aspects of the disorder remain uncertain and debatable. For example, ongoing debate surrounds which specific conditions fall under this diagnostic category and how to best differentiate BFRBs from conditions such as nonsuicidal self-injury (NSSI). The current article presents results from a study of experts' opinions on diagnostic criteria and descriptions, with the goal of refining the diagnostic criteria. MethodWe contacted experts on BFRB via various sources and invited them to an online survey on the phenomenology, classification, and differential diagnosis of BFRB. We also asked about possible alternative syndrome labels (e.g., body-focused habit). ResultsData from the final sample of 50 experts demonstrates that most experts agree with the present classification of BFRB as an obsessive-compulsive and related disorder and recommend retaining the labels BFRB or BFRBD. The experts considered the following conditions BFRB, with an agreement of over 60 %: trichotillomania, skin picking, dermatophagia, nail biting, and lip-cheek biting. Mixed results emerged for awake bruxism and thumb sucking in adults. In contrast, only a minority regarded night bruxism and knuckle cracking as BFRB. To differentiate BFRB from NSSI, the experts noted that the motive behind the urge (self-harm/injury versus release of tension) should be considered. Analyses of a sub-sample of experts with at least six years of clinical and/or research experience yielded results compatible with those of the entire sample. DiscussionThe survey supports the usefulness of the BFRB or BFRBD diagnostic entity. However, some criteria require further refinement. Future editions of the DSM should more explicitly delineate which conditions qualify as BFRB. Furthermore, it is important to give more attention to the primary motivation behind BFRB to distinguish it from NSSI and potentially from stereotypic movement behavior.

Impact of the diagnostic label for a low-risk prostate lesion: protocol for two online factorial randomised experiments

IntroductionMany types of prostate cancer present minimal risk to a man’s lifespan or well-being, but existing terminology makes it difficult for men to distinguish these from high-risk prostate cancers. This...

Chronic kidney disease - alternative labels used by Australian general practitioners. A qualitative interview study.

Guidelines for terminology defining chronic kidney disease (CKD) have been in use for 20 years. Age is not currently considered in the guideline definition of CKD. In previous studies, General Practitioners (GPs) have been reluctant to give older patients the label of CKD. Our study aimed to determine what language general practitioners are using to describe or label chronic kidney disease with their older patients, and to explore the reasons for their use of alternative language. This was a descriptive qualitative interview study of Australian GPs. Twenty-seven GPs were recruited via email and interviewed regarding their management of CKD., GPs were asked what language and terminology they used when discussing a diagnosis of CKD with their older patients. "Labelling of CKD", the language that GPs use when talking about CKD with their patients, emerged as a major theme from the initial GP interviews. Sub-themes emerged, including: types of labels, alternate labels and rationale for alternate labelling. GPs used descriptions of "reduced kidney function" to explain CKD to their patients, either in parallel with the diagnosis of CKD or instead of it. GPs had concerns about the words "chronic" and "disease" and used different terminology to explain these words to patients when diagnosing them with CKD. GPs use alternative descriptions to explain mild decrease in kidney function with older patients. Alternative labels that denote level of risk to older patients, without creating unnecessary concern about normal age-related kidney function need to be explored.

Outlier Detection by Energy Minimization in Quantized Residual Preference Space for Geometric Model Fitting

Outliers significantly impact the accuracy of geometric model fitting. Previous approaches to handling outliers have involved threshold selection and scale estimation. However, many scale estimators assume that the inlier distribution follows a Gaussian model, which often does not accurately represent cases in geometric model fitting. Outliers, defined as points with large residuals to all true models, exhibit similar characteristics to high values in quantized residual preferences, thus causing outliers to cluster away from inliers in quantized residual preference space. In this paper, we leverage this consensus among outliers in quantized residual preference space by extending energy minimization to combine model error and spatial smoothness for outlier detection. The outlier detection process based on energy minimization follows an alternate sampling and labeling framework. Subsequently, an ordinary energy minimization method is employed to optimize inlier labels, thereby following the alternate sampling and labeling framework. Experimental results demonstrate that the energy minimization-based outlier detection method effectively identifies most outliers in the data. Additionally, the proposed energy minimization-based inlier segmentation accurately segments inliers into different models. Overall, the performance of the proposed method surpasses that of most state-of-the-art methods.

Predicting Perceived Gloss: Do Weak Labels Suffice?

AbstractEstimating perceptual attributes of materials directly from images is a challenging task due to their complex, not fully‐understood interactions with external factors, such as geometry and lighting. Supervised deep learning models have recently been shown to outperform traditional approaches, but rely on large datasets of human‐annotated images for accurate perception predictions. Obtaining reliable annotations is a costly endeavor, aggravated by the limited ability of these models to generalise to different aspects of appearance. In this work, we show how a much smaller set of human annotations (“strong labels”) can be effectively augmented with automatically derived “weak labels” in the context of learning a low‐dimensional image‐computable gloss metric. We evaluate three alternative weak labels for predicting human gloss perception from limited annotated data. Incorporating weak labels enhances our gloss prediction beyond the current state of the art. Moreover, it enables a substantial reduction in human annotation costs without sacrificing accuracy, whether working with rendered images or real photographs.

Investigations on Diamond-NV-Centers as Alternative Labels in STED Microscopy

We investigate diamond nitrogen-vacancy (NV) centers as alternative labels in stimulated emission depletion (STED) microscopy. To this end, artificial diamond is used as a substrate and Raman spectroscopy in photoluminescence (PL) mode is performed for clearly identifying the emission wavelengths of the NV centers. With the aid of a STED microscopy system, we imaged a random feature on substrate surface with the NV-centers in STED and confocal mode. Our first measurements indicate that the combination of NV centers and STED is very promising for resolving the structures and can be further extended to nanoscale structures applied on the diamond substrates.

Managing a policy paradox? Responses to textual warning labels on E-cigarette advertisements among U.S. national samples of youth overall and adults who smoke or vape

ContextCurrent use and potential future uptake of e-cigarettes among youth remain public health concerns in the U.S., even as people who smoke combustible cigarettes could benefit from switching completely to e-cigarettes. The U.S. Food and Drug Administration (FDA) is considering alternative warning messages, but warnings that discourage youth from use may also deter people who smoke from switching. This study tests ten pre-registered hypotheses on effects of warning messages with national samples of youth overall and adults who smoke and/or vape. MethodsNORC recruited 1639 adults (ages 18+) who smoke, vape, or use both products, from their probability-sampled AmeriSpeak Panel and augmented their AmeriSpeak Teen Panel with Lucid's nonprobability opt-in panel to recruit 1217 youth (ages 14–17) to participate in a web-based survey experiment. We randomly assigned respondents to view one of five warning label conditions and respond to measures of their e-cigarette risk beliefs, willingness to use e-cigarettes, and (among people who smoke or vape) considerations to quit these products. FindingsRelative to the current FDA warning about nicotine, warning messages about the harms of e-cigarette use for youth brain development did not influence risk beliefs or reduce willingness to use these products among youth. Brain development warning messages did increase beliefs about these harms among adults but did not increase quit considerations among people who vape, relative to the FDA warning. Warning messages with information about chemical constituents of vaping products and the harm of these chemicals produced higher e-cigarette quit considerations than did the FDA warning among adults who vape. ConclusionPotential alternative warning label messages were largely ineffective relative to the current FDA warning about nicotine, though limited evidence suggests some potential for chemical + harm messaging to encourage people who use both e-cigarettes and cigarettes to consider quitting both.

A - 5 Patients' Understanding of Neuropsychological Performance Descriptors: a Pilot Study.

Descriptive labels to communicate neuropsychological performance are an integral part of neuropsychological reports. Although the American Academy of Clinical Neuropsychology (AACN) developed a consensus statement on uniform descriptive labels to standardize use of performance descriptors, patients' understanding of these labels is unclear. This pilot study sought to evaluate patient understanding of neuropsychological performance descriptors. Patients (N = 47) completed a survey consisting of 13 questions evaluating AACN's uniform label system and an alternative, patient-centered label system (PCL) designed to improve patients' understanding of scores. Questions assessed knowledge of label descriptions and their associated percentiles (e.g., average = 25-75th %ile), and the relative relationship between labels. Paired t-tests were used to determine if patients were more accurate in correctly understanding the AACN vs. PCL descriptive labels. Patients were significantly more accurate in understanding PCL labels (M = 1.38, SD = 0.49) than AACN's labels (M = 1.72, SD = 0.45), t = 4.08, p.05). Overall, patients demonstrated difficulty accurately understanding percentiles (M correct responses =1.36 of 5). Results demonstrated that patients may not adequately understand AACN's descriptive label system or other methods used to describe scores (i.e., percentiles). An improved understanding of labels was seen with an alternative label system (PCL), although response accuracy was still weak. Future studies should assess understanding of performance descriptors among caregivers and healthcare providers, and also examine patient-centric methods for presenting neuropsychological results.

Biodistribution and toxicity assessment of methoxyphenyl phosphonium carbosilane dendrimers in 2D and 3D cell cultures of human cancer cells and zebrafish embryos

The consideration of human and environmental exposure to dendrimers, including cytotoxicity, acute toxicity, and cell and tissue accumulation, is essential due to their significant potential for various biomedical applications. This study aimed to evaluate the biodistribution and toxicity of a novel methoxyphenyl phosphonium carbosilane dendrimer, a potential mitochondria-targeting vector for cancer therapeutics, in 2D and 3D cancer cell cultures and zebrafish embryos. We assessed its cytotoxicity (via MTT, ATP, and Spheroid growth inhibition assays) and cellular biodistribution. The dendrimer cytotoxicity was higher in cancer cells, likely due to its specific targeting to the mitochondrial compartment. In vivo studies using zebrafish demonstrated dendrimer distribution within the vascular and gastrointestinal systems, indicating a biodistribution profile that may be beneficial for systemic therapeutic delivery strategies. The methoxyphenyl phosphonium carbosilane dendrimer shows promise for applications in cancer cell delivery, but additional studies are required to confirm these findings using alternative labelling methods and more physiologically relevant models. Our results contribute to the growing body of evidence supporting the potential of carbosilane dendrimers as vectors for cancer therapeutics.

SiR-DNA/SiR-Hoechst-induced chromosome entanglement generates severe anaphase bridges and DNA damage.

SiR-DNA/SiR-Hoechst is a far-red fluorescent DNA probe that is routinely used for live-cell imaging of cell nuclei in interphase and chromosomes during mitosis. Despite being reported to induce DNA damage, SiR-DNA has been used in more than 300 research articles, covering topics like mitosis, chromatin biology, cancer research, cytoskeletal research, and DNA damage response. Here, we used live-cell imaging to perform a comprehensive analysis of the effects of SiR-DNA on mitosis of four human cell lines (RPE-1, DLD-1, HeLa, and U2OS). We report a dose-, time-, and light-dependent effect of SiR-DNA on chromosome segregation. We found that, upon the exposure to light during imaging, nanomolar concentrations of SiR-DNA induce non-centromeric chromosome entanglement that severely impairs sister chromatid segregation and spindle elongation during anaphase. This causes DNA damage that is passed forward to the following cell cycle, thereby having a detrimental effect on genome integrity. Our findings highlight the drawbacks in using SiR-DNA for investigation of late mitotic events and DNA damage-related topics and urge the use of alternative labeling strategies to study these processes.

A lightweight ontology for landmarks to assist rescue in mountainous areas

Abstract. When people are injured or lost in mountains during outdoor activities and when web-based locations are not available, they locate themselves by describing their environment, routes and activities. The description of their location is done using landmarks and spatial locations (e.g., “I am located in front of Punay Lake”, “I am near a protected area”). Landmarks used can be named (e.g., “Punay Lake”) or unnamed if the landmark has no name or if the victim does not know it (e.g., "area lake"). Landmarks are represented in geographic databases by name (if possible), type and geometry. To reduce the heterogeneity of landmark types present in oral language and geographic databases representing landmarks, and thus improve locating victims, our goal is to define a controlled vocabulary for landmarks. In this research, we present a lightweight ontology (i.e. ontology having generally less complexity and does not express formal constraints) of landmarks, named Landmark Ontology (OOR), describing landmark types. It is an application ontology, i.e. it is designed to support mountain rescue operations. The ontology construction is adapted from the SAMOD methodology for engineering ontology development and involves researchers and experts from mountain rescue teams. The construction of OOR is composed of four main phases: knowledge acquisition, conceptual formalisation, implementation, and testing. The implementation phase is carried out by an iterative and collaborative approach and using four formalised sources of knowledge (a landmark and a landform ontologies, and two other domain vocabularies), an un-formalised taxonomy of outdoor activities, and five authoritative and volunteered geographic information sources representing geographic data. The landmarks ontology contains 543 classes associated with 1739 labels: 1086 prefLabel (preferential label) in French and English, 321 altLabel (alternative label) in French, and 332 altLabel in English. The depth of the ontology varies from four for land cover, hydrological and land subdivision landmark types), to six for landform types, and eight for building types. Although the use of ontology is broader, in this paper we illustrate and test its use through three applications in the context of mountain rescue operations: semantic mapping, data instantiation and data matching.

AnnoBERT: Effectively Representing Multiple Annotators’ Label Choices to Improve Hate Speech Detection

Supervised machine learning approaches often rely on a "ground truth" label. However, obtaining one label through majority voting ignores the important subjectivity information in tasks such hate speech detection. Existing neural network models principally regard labels as categorical variables, while ignoring the semantic information in diverse label texts. In this paper, we propose AnnoBERT, a first-of-its-kind architecture integrating annotator characteristics and label text with a transformer-based model to detect hate speech, with unique representations based on each annotator's characteristics via Collaborative Topic Regression (CTR) and integrate label text to enrich textual representations. During training, the model associates annotators with their label choices given a piece of text; during evaluation, when label information is not available, the model predicts the aggregated label given by the participating annotators by utilising the learnt association. The proposed approach displayed an advantage in detecting hate speech, especially in the minority class and edge cases with annotator disagreement. Improvement in the overall performance is the largest when the dataset is more label-imbalanced, suggesting its practical value in identifying real-world hate speech, as the volume of hate speech in-the-wild is extremely small on social media, when compared with normal (non-hate) speech. Through ablation studies, we show the relative contributions of annotator embeddings and label text to the model performance, and tested a range of alternative annotator embeddings and label text combinations.

Manufacturer encroachment on a green supply chain with environmental labeling

AbstractThis paper investigates manufacturer encroachment on a green supply chain wherein alternative environmental labels are utilized to disclose the hidden product greenness attribute. We show that both self‐ and government labels facilitate and adjust the promotion effect of encroachment on product greenness, stimulating green demand and retail prices for profitability improvement and raising wholesale prices for investment sharing. The difference is that self‐labeling's low credibility and complete self‐interest features only induce inferior greenness increments and coordination effects. Government labeling outperforms self‐labeling in simultaneously optimizing the interests of the manufacturer, retailer, and society, presuming the benefits of greenness improvement reimburse investments.

Less than a Lingua franca but more than just ‘any other language’: conceptualising German in the Baltic States as ‘additional language of society’

ABSTRACT This paper discusses contemporary societal roles of German in the Baltic states (Latvia, Estonia, Lithuania). Speaker and learner statistics and a summary of sociolinguistic research (Linguistic Landscapes, language learning motivation, language policies, international roles of languages) suggest that German has by far fewer speakers and functions than the national languages, English, and Russian, and it is not a dominant language in the contemporary Baltics anymore. However, German is ahead of ‘any other language’ in terms of users and societal roles as a frequent language in education, of economic relations, as a historical lingua franca, and a language of traditional and new minorities. Highly diverse groups of users and language policy actors form a ‘coalition of interested parties’ which creates niches which guarantee German a frequent use. In the light of the abundance of its functions, the paper suggests the concept ‘additional language of society’ for a variety such as German in the Baltics – since there seems to be no adequate alternative labelling which would do justice to all societal roles. The paper argues that this concept may also be used for languages in similar societal situations and, not least, be useful in language marketing and the promotion of multilingualism.

What is a mental disorder? Evaluating the lay concept of Mental Ill Health in the United States

PurposeHow “mental disorder” should be defined has been the focus of extensive theoretical and philosophical debate, but how the concept is understood by laypeople has received much less attention. The study aimed to examine the content (distinctive features and inclusiveness) of these concepts, their degree of correspondence to the DSM-5 definition, and whether alternative concept labels (“mental disorder”, “mental illness”, “mental health problem”, “psychological issue”) have similar or different meanings.MethodsWe investigated concepts of mental disorder in a nationally representative sample of 600 U.S. residents. Subsets of participants made judgments about vignettes describing people with 37 DSM-5 disorders and 24 non-DSM phenomena including neurological conditions, character flaws, bad habits, and culture-specific syndromes.ResultsFindings indicated that concepts of mental disorder were primarily based on judgments that a condition is associated with emotional distress and impairment, and that it is rare and aberrant. Disorder judgments were only weakly associated with the DSM-5: many DSM-5 conditions were not judged to be disorders and many non-DSM conditions were so judged. “Mental disorder”, “mental illness”, and “mental health problem” were effectively identical in meaning, but “psychological issue” was somewhat more inclusive, capturing a broader range of conditions.ConclusionThese findings clarify important issues surrounding how laypeople conceptualize mental disorder. Our findings point to some significant points of disagreement between professional and public understandings of disorder, while also establishing that laypeople’s concepts of mental disorder are systematic and structured.

Food Thermal Labels are a Source of Dietary Exposure to Bisphenol S and Other Color Developers.

To test the hypothesis that migration from the thermal labels on plastic film packaging is a major source of exposure to bisphenols and alternative color developers in food, we analyzed 140 packaging materials from packaged fresh food purchased in North America. No bisphenol A (BPA) was detected in either the packaging samples or thermal labels. However, significant amounts of bisphenol S (BPS) and alternative color developers (up to 214 μg/cm2) were present in thermal labels; their relative occurrence varied among stores. In a controlled experiment, we wrapped fish in film with a thermal label for 5 days at 4 °C. The fish in contact with the label contained BPS (≤1140 ng/g wet weight [ww]), 4-hydroxyphenyl 4-isoprooxyphenylsulfone (D-8) (≤230 ng/g ww), bis(2-chloroethyl)ether-4,4'-dihydroxydiphenyl sulfone monomer (D-90) (≤3.41 ng/g ww), and/or Pergafast-201 (≤1.87 ng/g ww). The corresponding film samples were then tested using migration cells for 10 days; significantly higher BPS migration was observed systematically from the films with thermal labels compared to plain films. This study provides evidence, for the first time, that BPS and alternative thermal label color developers migrate from packaging materials into food. Further, BPS migration significantly exceeded the European Union Specific Migration Limit (50 ng/g ww), suggesting that further risk assessment studies are warranted.