Uncovering the essence of diverse media biases from the semantic embedding space Humanities and Social Sciences Communications

The third typical meaning pattern that the NP in the NP de VP construction denotes pertains to zhidu ‘regulations’ and tixi ‘systems’ (except for some irrelevant ones in either of the two meaning patterns). The former further incorporates biaozhun ‘standard’, zhengce ‘policy’, zhidu ‘regulation’, quanli ‘rights’, gongneng ‘function’, and zuoyong ‘function’; the latter incorporates such members as jigou ‘organization’, tixi ‘systme’, tizhi ‘regulation’, and jizhi ‘mechanism’. Investigation of their covarying collexemes in the VP slot demonstrates that they cooccur significantly with verbs that denote senses of “implementation” and “establishment” such as guanche ‘enact’, zhiding ‘implement’, xingshi ‘perform’, and jianli ‘establish’, etc. This could be exemplified by the significant cooccurrences of zhidu ‘regulation’ and guanche ‘enact’ in (11a), and tizhi ‘regulation’ and jianli ‘establish’ in (11b) which is rewritten from example (3). In the same vein, the meaning patterns of NP in the NP de VP construction could also be clustered by referring to their corresponding covarying collexemes in the VP slot of the construction. The second typical meaning pattern of the NP de VP construction pairs the sense of “systems” in the NP slot with the sense of “establishment” in the VP slot.

According to Equation (1), Calculate the global field power (GFP) of the subject at each time point, and extract the topography corresponding to the GFP peak to construct a set of topographies. Up to this point, the multichannel EEG signal has been decomposed into a time sequence comprising K alternating microstates. The microstate template Γk can be obtained by solving the above equation by clustering algorithm or Lagrange multiplier. Experimental results and their corresponding discussions are found in Sections III and, followed by the conclusion in Section IV.

You can foun additiona information about ai customer service and artificial intelligence and NLP. The MOX2-5 dataset featured in this article offers preprocessed daily physical activity data. Finally, this study considers the generalization of the proposed method to cross-subject problems. In the previous classification task, we used a 10-fold cross-validation approach where the data from all subjects were mixed and randomly disrupted to verify the recognition accuracy. In order to more fully assess the generalizability of the method proposed in this paper, we used a leave-one-out method for validating the performance of the method in cross-subject schizophrenia recognition.

Further, a few cases are eventually shifted into nominal phrases, not being a clause with participants and circumstances anymore, thus falling under the other types of nominalization. For example, “四维不张, 国乃灭亡” (Xi, 2014a, p. 168) was translated as “Propriety, righteousness, honesty and a sense of shame—the four anchors of our moral foundation, and a question of life and death for the country” (Xi, 2014b, p. 188). The whole translated sentence consists of several nominal phrases, downgrading the rank of a clause to the word group. However, as the translation itself is not a clause, there are of course no participant and circumstance element components in it.

Another important prototypical meaning pattern with respect to the VP in the NP de VP construction is concerned with the reporting verbs. In other words, reporting verbs ChatGPT are also likely to enter the VP slot of the construction. Typical reporting verbs of this type include baodao ‘report’, tichu ‘propose’, and biaoda ‘express’.

Diamond Dust: A Dream Solution to Climate Change

After successfully saving the data, additional steps may take place depending on the settings defined for the instrument. Sending email notifications (both for the respondent and the research team), verifying the duplicity of records, and the instant lock of the saved record (to avoid changes in the data) are possible extra actions. In the designing process, there is a particularity related to multiple-selection questions (checkboxes).

Greek philosophers in the 5th century bc who debated the origins of human language were the first in the West to be concerned with linguistic theory. The first complete Greek grammar, written by Dionysus Thrax in the 1st century bc, was a model for Roman grammarians, whose work led to the medieval and Renaissance vernacular grammars. However, finding answers requires querying, extracting, and aggregating data from multiple tables using joins, filters, or other complex operations. The user must understand the underlying data structure and complex relations between tables — and be familiar with query languages such as SQL. Without this knowledge, business users must rely on data analysts to provide answers, creating dependencies and delays and eroding trust in insights received secondhand.

Rather, the Triangle model10,11 (see Fig. 1) proposes that what people often think of as lexical access is just a type of semantic processing. In that model, words can be read aloud two ways, via a semantically mediated route and via a non-semantic orthography-to-phonology (OtP) route. Both routes can potentially read all words and the OtP route can also impute pronunciations of novel words (nonwords). These dynamics differ to CDP where the lexical route can potentially read all words but the sublexical route can only correctly impute the phonology of words with relatively simple spelling–sound relationships. (8)–(11), the generalization ability of the ILDA model is stronger when the Perplexity is smaller. Namely, the optimal topic quantity K is determined when Perplexity-AverKL is the smallest.

Meaning pattern of “achievement”

The authors gratefully acknowledge Mikkel Werling’s help with study conception, data cleaning and data analysis. Parental leave is often structured as a family entitlement that mothers and fathers can share. However, globally, mothers take more leave than fathers, which is a key contributor to labour market inequality between men and women1,2,3. As a result, there has been considerable interest in policy reforms that incentivize parents to share parental leave more equally.

For example, future studies could consider exploring other characteristics of news and textual variables connected to psychological aspects of natural language use73 or consider measures such as language concreteness74. Our work has important implications to cognitive and computational approaches to characterizing semantic change. Separate lines of research ranging from cognitive science to computational linguistics have presented the converging view that word meaning often changes in incremental as opposed to abrupt ways (Frermann and Lapata, 2016; Bamler and Mandt, 2017; Ramiro et al., 2018). Our current analysis paints a more complex picture of semantic change by suggesting that incremental or similarity-based processes alone are not sufficient to account for the diverse range of attested cases of semantic change. However, it is likely that semantic change relies on a combination of cognitive mechanisms that identify both surface similarity and structural (or analogy-based) similarity (Gentner, 1983) in meaning space. A fundamental challenge for future research is how to integrate these different kinds of processes in a coherent formal framework for generating the diverse range of semantic changes across languages.

Detecting Parkinson’s disease and its cognitive phenotypes via automated semantic analyses of action stories

In short, Ukrainians want weapons in order to win, while most Europeans send weapons hoping this will help lead to an acceptable eventual settlement. This division is also reflected in public opinion on the idea of Ukraine joining the EU and NATO. Ukrainian citizens seem to regard membership of both organisations as a recognition of the bravery of their fight. Meanwhile, in Western capitals the membership question tends to be discussed as part of an eventual compromise deal with Russia.

We explore mechanisms for identifying and ranking the most relevant tweets related to a specific search term. We use hurricane Irma as a use case and demonstrate methods for identifying relevant tweets by optimizing different parameters. It has been observed within the vector constructs for Word2Vec that vector operations, such as addition and subtraction, yield meaning10,26. This was used as the predicate for interpreting the meaning of a tweet as the sum of its component word vectors.

Last, participants completed a short questionnaire about how distracted they were during the task. Participants received a link to the second part of the experiment the following day; if they did not complete the Day 2 session within 28 h (i.e. before they had a second night of sleep), they were excluded from all analyses. The Day 2 session (Fig. 1) began with testing of all word pairs (“final test”), and then participants performed another set of similarity judgements using the SWAT protocol. Testing was performed prior to the SWAT protocol on Day 2 to prevent the possibility that words encountered during the SWAT trials would trigger additional retrieval practice or other rehearsal, which could have influenced final test performance in unpredictable ways.

The questionnaire in Ukraine included several questions that were not asked elsewhere. Overall, the graphs in this paper display data for all the countries in which the respective question was asked. This report is based on a public opinion poll of adult populations (aged 18 and over) conducted in May 2024 in 15 countries (Bulgaria, the Czech Republic, Estonia, France, Germany, Great Britain, Greece, Italy, Poland, Portugal, the Netherlands, Spain, Sweden, Switzerland, and Ukraine). As the war progresses through its third year, public opinion has changed strikingly little, even as the fighting has entered a new phase. The question is whether this stasis comes from a fear of a changing reality or a deeper resilience in the face of aggression. If it is the former – where Ukrainians profess their faith in victory and Europeans say they will back them – with neither side really believing it, then this position may collapse in the face of Russian success or a Trump ‘peace plan’.

As for the analytical unit for the fields of activity, one single sentence can serve as a self-contained unit. Therefore, ST and TT collected in Xi’s books were analyzed in the unit of a sentence, being placed in the specific context of the sentence before the identification of fields, thus ensuring the effectiveness of the data. What is also instructive from the previous studies is that contextual elements should be taken into consideration, as literary translation in political texts is not the same as pure literary translation. Further, the paucity of studies on the ACPP translation from the angle of reproducing its experiential meaning leaves room for exploration. SFL has been recognized as an important research resource in translation studies since the 1950s when Halliday’s SFL theory was still in its infancy, and even the creation of Systemic Functional Translation Studies (SFTS) for the applied and theoretical research influenced by SFL.

Changes from one value to the next for all parameter tests were measurable, but the variation rarely exceeded 0.02 in the subsequent calculation of AU-ROC (see Table 6). The difference between 0 and 1 for the negative sampling value showed a substantial increase from 0.560 to 0.854 for the Dot Product Formula. The 0.854 for the Dot Product formula below also represents the highest AU-ROC score for all parameter tests. ChatGPT App The remaining AU-ROC values for 2 through 9 negatively sampled words were also greater than the corresponding value for 0. This indicated that including a minimal number of negative context words in the training has an overall positive effect on the accuracy of the neural network. In the Word2Vec module, there are two different methods of training the vector model, and they are nearly opposites of each other.

However, there is a feature to instantly send collected data to an external server (data is sent in JSON standard). This feature is handy when using the system only for data collection, which is the intention of this work, and because it eliminates the need to develop a client to extract data. Once the system’s deficiencies are overcome, a higher score is expected in future usability and satisfaction tests. The CSUQ questionnaire allowed the authors to verify the overall satisfaction of active users and the System Usefulness, Information Quality, and Interface Quality subscales. Even though it got a small number of responses, it still represents a good portion of the active user database.

4. Reconstruction by a phylogenetic comparative model

In general, a time series is said to Granger‐cause another time series if the former has incremental predictive power on the latter. Therefore, Granger causality provides an indication of whether one event or variable occurs prior to another. We also looked at the cross-correlation of the target series with our predictors (i.e., ERKs series) to see if they were in phase (positive signs of cross-correlation) or out of phase (negative sign)60,61.

Therefore, the customer requirements expression are satisfactory when they are consistent with the cognition of designers. Latent product functional, behavioral and structural requirements are obtained through an analogy-inspired VPA experiment. Those feasible and innovative customer requirements will provide support for designers. Our emphasis on exploring crosslinguistically shared regularity in semantic change is related to both theoretical and computational diachronic studies of word meaning. For instance, recent work has explored regularity (Bowern, 2008) and taken a functional approach in the study of grammaticalization (Hopper and Traugott, 2003).

• These existing literatures together suggested a higher rate of journal and article coverage in Scopus than in WoS.
• Latent Semantic Analysis (LSA) is a popular, dimensionality-reduction techniques that follows the same method as Singular Value Decomposition.
• Because stain area is specific and more biologically targeted than the rough annotations that incorporate empty lumens and mislabeled features, the models’ immunostain Spearman correlation scores are much more reflective of their overall accuracy and sensitivity.

However, it’s crucial to recognize that this approach, despite its power, does not replicate human semantic understanding. LLMs lack true comprehension, real-world grounding, and the ability to reason about truth and reference in the way humans do. As research continues, bridging the gap between distributional and traditional semantics remains an important challenge in artificial intelligence and cognitive science. With customer support now including more web-based video calls, there is also an increasing amount of video training data starting to appear. NLP libraries capable of performing sentiment analysis include HuggingFace, SpaCy, Flair, and AllenNLP. In addition, some low-code machine language tools also support sentiment analysis, including PyCaret and Fast.AI.

Specifically, we assume that there are underlying topics when considering a media outlet’s event selection bias. If a media focuses on a topic, it will tend to report events related to that topic and otherwise ignore them. Therefore, media outlets sharing similar event selection biases (i.e., tend to report events about similar topics) will be close semantics analysis to each other in the latent topic space, which provides a good opportunity for us to study media bias (See Methods and Results for details). The proposed ontology with integrated SSN representation enables more detailed modeling and querying of physical activity observations, including activity level, number of steps, sensors, and observation time.

In natural language processing, semantic analysis helps machines grasp the nuances of human language, such as irony, sarcasm, or ambiguity. It is a critical component of technologies that rely on language understanding, like text analysis, language translation, and voice recognition systems. As mentioned above, our proposed framework examines media bias from two distinct but highly relevant perspectives.

Experimental set-up

The experimental results indicate that the model trained using the microstate features proposed in this paper performs well in the recognition task of schizophrenia, and is able to distinguish between positive and negative cases effectively. This article focuses on the semantics expressed by the frequency of microstate subsequences. From the figure, it can be clearly observed that the quality features are significantly discriminative in the identification of SCZ. In terms of Correlation and Explanation, the values are significantly higher when the template is consistent with the data than in the inconsistent combination. In contrast, the residual and Dispersion were significantly lower in consistent combinations than in inconsistent combinations. These results provide an important reference for the application of microstate sequence quality features in the identification of SCZ, as well as a beneficial reference for future research and clinical applications.

• Second, the difference in logical structure between the two languages can also result in the rank shift of nominalization.
• A 3D projection view of the segmented ER structure of the sample in Supplementary Video 13.
• Although researchers as such have uncovered the semantic relationship between the NP and the VP in the construction, they do not count on the typical meanings that these elements could denote or how these meanings could be patterned.
• Comparisons of different scalar formulas were conducted across several tuning parameters.
• An example of the time series within an ROI is shown in supplementary material section A.

(D) The relation between different nodes in the network of SFM, social support, and self-acceptance as well as the covariates. (A) The network model of social support and self-acceptance with age and gender controlled as covariates. To examine the accuracy and stability of the network models, the R package bootnet was employed. To verify the accuracy, we evaluated the bootstrapped confidence intervals (95% CIs) by using the nonparametric bootstrap. In this part, the narrower the CIs are, the more accurate and reliable the network models are. Moreover, to test whether there exists a significant difference between edge weights and BEI, the bootstrapped difference test was employed.

1. The enigmatic domain of semantic evolution and change

Hence, further studies are encouraged to delve into sentence-level dynamic exploration of how different semantic elements interact within argument structures. As for semantic adjuncts, it is worth noting that the average number of discourse markers (DIS) in CT is significantly bigger than that in ES, indicative of the translator’s inclination to enhance the coherence and thus the necessity to make certain contextual logical relationships explicit. Additionally, the number of adverbials (ADV) in CT is significantly bigger than that in ES while the number of manners (MNR) in CT is significantly smaller. For a more detailed view of the differences in syntactic subsumption between CT and ES, the current study analyzed the features of several important semantic roles. To begin with, Leneve’s tests were conducted on each index to see whether there was a homogeneity of variance.

In summary, Wu-Palmer Similarity or Lin Similarity actually provide a way to quantify and measure I(E) in Formula (1). By calculating the two values, we can approximate the explicit level of H to T, or in other words, the semantic depth of the original sentence H. A smaller the value of Wu-Palmer Similarity or Lin Similarity indicates a more explicit predicate. The amount of extra information can also be interpreted as the distinction between implicit and explicit information, which can be captured through textual entailment. Take the semantic subsumption between T3 and H3 for example, I(E) is the information gap between the two predicates “eat” and “devour”.

Detailed information about data segmentation will be presented in the experimental section. (3) Determining the appropriate length of microstate sequences is imperative for efficient feature extraction and recognition and warrants further investigation. Sequences that are too short may not accurately capture certain microstate features, thus impacting the accuracy, while sequences that are too long may increase the computational burden and processing time. In the current study, we used R (version 4.3.2) for the data analysis (Team R.C, 2023). To start with, descriptive analysis to describe the basic information of participants in the current study was conducted.

In one case, this is determined by using a narrowly defined set of related tweets to classify a tweet as election related. While the objective here is similar, the approach for this paper is to provide a mechanism for broader search criteria, not necessarily restricted to a single event. By training on data contemporaneous with potentially relevant search criteria, the algorithm seeks wider capability and flexibility, both in its interpretation of meaning and relevance. Social media content, like that contained in Twitter, exhibits many of the pitfalls of processing natural language and presents unique challenges depending on objective.

The distinctive aspect of our textual entailment analysis is that we take a given sentence as H and create its T by changing the predicate in the sentence into its root hypernym. In this way we manually create a determined entailment relationship between T and H. Based on this methodology, the extra information I(E) in Formula (1) can be approximated by the distance between the original predicate and its root hypernym. Then the distance can be quantified as 1 minus the Wu-Palmer Similarity or Lin Similarity between the original predicate and its root hypernym.

Semantic analysis methods will provide companies the ability to understand the meaning of the text and achieve comprehension and communication levels that are at par with humans. Cdiscount, an online retailer of goods and services, uses semantic analysis to analyze and understand online customer reviews. When a user purchases an item on the ecommerce site, they can potentially give post-purchase feedback for their activity. This allows Cdiscount to focus on improving by studying consumer reviews and detecting their satisfaction or dissatisfaction with the company’s products.

By comparison, the deep learning models take less than an hour depending on section size and graphics process unit (GPU) performance. Human annotation of the data is even slower, taking days to weeks for a single section and can have high variability between annotators. In addition, it can be difficult to get access to an expert with pathology certification necessary for differentiating the morphologies. This study also found that compression, rather than expansion of processes, is the tendency in translating the ACPP in political texts, including the omission of processes and the compression of several process types into one.

This capability is especially desirable in health information systems (HIS) due to the heterogeneity of the medical language and health-related concepts14. In the case of tuberculosis (TB), an infectious and neglected disease10, the resources for research may be lacking, and the costs of using an EDC could be a limitation. The scenario is aggravated by the fact that Brazil is among the top 30 countries with the highest TB burden11. Therefore, making data available for further data-driven studies is crucial to underpinning the development of new evidence-based decision-making tools. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.