Distinct Words Research Articles

A Pseudo-Value Approach to Analyze the Semantic Similarity of the Speech of Children With and Without Autism Spectrum Disorder.

Conversational impairments are well known among people with autism spectrum disorder (ASD), but their measurement requires time-consuming manual annotation of language samples. Natural language processing (NLP) has shown promise in identifying semantic difficulties when compared to clinician-annotated reference transcripts. Our goal was to develop a novel measure of lexico-semantic similarity – based on recent work in natural language processing (NLP) and recent applications of pseudo-value analysis – which could be applied to transcripts of children’s conversational language, without recourse to some ground-truth reference document. We hypothesized that: (a) semantic coherence, as measured by this method, would discriminate between children with and without ASD and (b) more variability would be found in the group with ASD. We used data from 70 4- to 8-year-old males with ASD (N = 38) or typically developing (TD; N = 32) enrolled in a language study. Participants were administered a battery of standardized diagnostic tests, including the Autism Diagnostic Observation Schedule (ADOS). ADOS was recorded and transcribed, and we analyzed children’s language output during the conversation/interview ADOS tasks. Transcripts were converted to vectors via a word2vec model trained on the Google News Corpus. Pairwise similarity across all subjects and a sample grand mean were calculated. Using a leave-one-out algorithm, a pseudo-value, detailed below, representing each subject’s contribution to the grand mean was generated. Means of pseudo-values were compared between the two groups. Analyses were co-varied for nonverbal IQ, mean length of utterance, and number of distinct word roots (NDR). Statistically significant differences were observed in means of pseudo-values between TD and ASD groups (p = 0.007). TD subjects had higher pseudo-value scores suggesting that similarity scores of TD subjects were more similar to the overall group mean. Variance of pseudo-values was greater in the ASD group. Nonverbal IQ, mean length of utterance, or NDR did not account for between group differences. The findings suggest that our pseudo-value-based method can be effectively used to identify specific semantic difficulties that characterize children with ASD without requiring a reference transcript.

Discretisation and continuity: The emergence of symbols in communication

Vocal signalling systems, as used by humans and various non-human animals, exhibit discrete and continuous properties that can naturally be used to express discrete and continuous information, such as distinct words to denote objects in the world and prosodic features to convey the emotions of the speaker. However, continuous aspects are not always expressed with the continuous properties of an utterance but are frequently categorised into discrete symbols. While the existence of symbols in communication is self-evident, the emergence of discretisation from a continuous space is not well understood. In this paper, we investigate the emergence of discrete symbols in regions with a continuous semantics by simulating the learning process of two agents that acquire a shared signalling system. The task is formalised as a reinforcement learning problem with a continuous form and meaning space. We identify two causes for the emergence of discretisation that do not originate in discrete semantics: 1) premature convergence to sub-optimal signalling conventions and 2) topological mismatch between the continuous form space and the continuous semantic space. The insights presented in this paper shed light on the origins of discrete symbols, whose existence is assumed by a large body of research concerned with the emergence of syntactic structures and meaning in language.

Our Words in a State of Emergency: Psychological-Linguistic Analysis of Utterances on the COVID-19 Situation in the Czech Republic.

The study focuses on psychological–linguistic analysis of utterances provided by N = 2522 respondents aged 18–89 years in the period of March–May 2020, for the research of JUPSYCOR (Psychological Impacts of the Coronavirus Epidemic in the Czech Republic). The utterances relate to the interpretation of the state of emergency, the COVID-19 epidemic, and its subjectively perceived impacts. Simultaneously, the study examines the relationship between the analysed texts and the results of the SEHW (Scales of Emotional Habitual Subjective Well-being) questionnaire, which determines the valence of experienced emotions. The aim of the study is to analyse the lexical and morphological layers of the utterances, especially which specific words resonated in the individual questions, what is their emotional load, and which linguistic features of the texts may refer to the respondents’ positive/negative emotional response. One of the outputs based on the results of the quantitative analyses determines that the most distinctive words are connected to negative emotions and most frequently relate to social environment, anxiety, and inhibition. Furthermore, the study proves a positive correlation between a fear scale and a higher occurrence of future tense and use of emotionally negatively loaded words, especially in women. Numerous differences among the individual age and gender cohorts were also proved. The significance of the study lies predominantly in the combination of the linguistic and psychological levels of the analysis, in the utilization of two mutually complementary utterances, and in the presentation of new insights on how people use words when they face an unexpected and emotionally disturbing situation.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12646-021-00613-y.

Overabundance and inflectional classification: Quantitative evidence from Czech

Overabundance is the situation where two or more distinct word forms fill the same cell in an inflectional paradigm (Thornton 2011). While this topic has received renewed attention in recent years, there are still several open questions regarding its properties and status. In this paper we present a new take on the matter. On the basis of a case study of the locative singular and instrumental plural of Czech nouns, we argue that there are at least two kinds of overabundance phenomena which should be distinguished, depending on whether overabundant behavior integrates in the inflection system or is orthogonal to it. The evidence for the distinction comes from a quantitative study of the way phonological, morphosyntactic, semantic, and sociolinguistic factors contribute to partially predicting whether a lexeme is overabundant and which form is used in different contexts.

Separating the Words of a Language by Counting Factors

For a given language L, we study the languages X such that for all distinct words u, v ∈ L, there exists a word x ∈ X that appears a different number of times as a factor in u and in v. In particular, we are interested in the following question: For which languages L does there exist a finite language X satisfying the above condition? We answer this question for all regular languages and for all sets of factors of infinite words.

Efficient representation and counting of antipower factors in words

A k-antipower (for k≥2) is a concatenation of k distinct words of the same length. Fici et al. (ICALP 2016) initiated the study of antipowers occurring as fragments of a word, whereas Badkobeh et al. (Inf. Process. Lett., 2018) presented first algorithms computing such fragments. We address two open problems originating from the latter work and propose efficient algorithms for counting and reporting fragments being k-antipowers. For a length-n word, our algorithms cost O(nklog⁡k) and O(nklog⁡k+C) time, respectively, where C is the number of reported fragments. We also show that the number of different k-antipower factors of a length-n word can be computed in O(nk4log⁡klog⁡n) time. Finally, we present an improved data structure that checks whether a given fragment is a k-antipower for a given integer k≥2. Our main algorithmic tools are runs and maximal gapped repeats.

‘What is psychiatry?’ – an exploration of the effect of a psychiatry summer school on school students’ attitudes towards psychiatry, through the medium of word clouds

AimsTo explore if attending a psychiatry summer school would change the understanding of school students as to what the word ‘Psychiatry’ represents.BackgroundThe Institute of Psychiatry, Psychology and Neuroscience (IoPPN) and the local mental health trust, South London and Maudsley NHS Foundation Trust (SLaM) ran a free five-day summer school for 16-year-old school students, who had just completed their GCSE exams, from state and private secondary schools within South-East London.MethodWe asked all 26 student attendees to anonymously write down as many single words relating to ‘Psychiatry’ as they could think of. They were given approximately 5 minutes to complete this and they were asked to do this at the beginning of the first day and at the end of the final day of the summer school. These words were then transcribed with the number of times each word was submitted being documented. This information was then formatted into a word cloud, with the size of the word varying according to how many times it had been submitted.ResultAt the start of the summer school, the students submitted a total of 208 words which included a total of 94 distinct words. Of these, the 2 most common were brain (n = 15) and mental (n = 10). At the end of the summer school, the students submitted a total of 199 words which included a total of 100 distinct words. The 2 most common were psychosis (n = 12) and forensic (n = 8). Of the words submitted pre-summer school, there were 8 distinct words that described positive attributes of psychiatry – such as ‘helping’. This increased to 17 distinct positive words post-summer school.ConclusionWe note from our outcomes that the number of words submitted by the students pre and post the summer school were similar but the words submitted most frequently differed. The most common words submitted post the summer school were more consistent with medical terminology than those submitted pre the summer school, which suggests that their knowledge of this had increased. The increase in the number of distinct positive words submitted at the end of the summer school implies that the students had a more positive view of psychiatry following the summer school.

Smart(er) Citations

Smart(er) Citations

Anti-power $j$-fixes of the Thue-Morse word

Recently, Fici, Restivo, Silva, and Zamboni introduced the notion of a $k$-anti-power, which is defined as a word of the form $w^{(1)} w^{(2)} \cdots w^{(k)}$, where $w^{(1)}, w^{(2)}, \ldots, w^{(k)}$ are distinct words of the same length. For an infinite word $w$ and a positive integer $k$, define $AP_j(w,k)$ to be the set of all integers $m$ such that $w_{j+1} w_{j+2} \cdots w_{j+km}$ is a $k$-anti-power, where $w_i$ denotes the $i$-th letter of $w$. Define also $\mathcal{F}_j(k) = (2 \mathbb{Z}^+ - 1) \cap AP_j(\mathbf{t},k)$, where $\mathbf{t}$ denotes the Thue-Morse word. For all $k \in \mathbb{Z}^+$, $\gamma_j(k) = \min (AP_j(\mathbf{t},k))$ is a well-defined positive integer, and for $k \in \mathbb{Z}^+$ sufficiently large, $\Gamma_j(k) = \sup ((2 \mathbb{Z}^+ -1) \setminus \mathcal{F}_j(k))$ is a well-defined odd positive integer. In his 2018 paper, Defant shows that $\gamma_0(k)$ and $\Gamma_0(k)$ grow linearly in $k$. We generalize Defant's methods to prove that $\gamma_j(k)$ and $\Gamma_j(k)$ grow linearly in $k$ for any nonnegative integer $j$. In particular, we show that $\displaystyle 1/10 \leq \liminf_{k \rightarrow \infty} (\gamma_j(k)/k) \leq 9/10$ and $\displaystyle 1/5 \leq \limsup_{k \rightarrow \infty} (\gamma_j(k)/k) \leq 3/2$. Additionally, we show that $\displaystyle \liminf_{k \rightarrow \infty} (\Gamma_j(k)/k) = 3/2$ and $\displaystyle \limsup_{k \rightarrow \infty} (\Gamma_j(k)/k) = 3$.

Prior context influences lexical competition when segmenting Chinese overlapping ambiguous strings

• Prior context affects the competition stage of word processing when reading Chinese. • Plausibility has an early effect on word segmentation. • The left-side word of an OAS is more likely to be segmented as a word. We report three eye-movement experiments that investigated the effect of prior sentence context on the processing of overlapping ambiguous strings (OASs) during Chinese reading. An OAS is a Chinese character string (ABC) in which the middle character can form a distinct word with both the character on its left (word AB) and on its right (word BC). In three experiments, we manipulated the extent to which the right-side word (BC) was plausible as an immediate continuation following the prior context; the left-side word AB was always plausible given the prior context, and the sentence continued in a manner that was compatible with word AB. Compared with a less plausible word BC, first-pass reading times on the OAS were longer with a more plausible word BC. The results suggest that in reading of Chinese strings with ambiguous word boundaries, plausibility influences an early stage of competition between words, rather than only a later checking process that occurs after the initial segmentation.

On optimal regimes of knowledge exchange: a model of recombinant growth and firm networks

The literature has documented two patterns of knowledge exchange: free sharing of knowledge and barter exchange. The former has been coined as collective invention, while the latter is observed in the form of R&D alliance. This study, for the first time, compares these two modes of cooperation in creating and diffusing new knowledge. Doing so, we take seriously the network character of knowledge and the skewed distribution of innovation size by proposing a novel model. In this model, knowledge is represented by distinct letters and words constructed thereof and accumulated by agents over time. Discovering new words agents recombine available knowledge pieces not randomly but following certain ideas, semi-definite structures on what words can be further constructed. We proceed by allocating agents in a network and allowing them to cooperate over direct ties either in a regime of collective invention or bilateral R&D alliances. We find networks with skewed degree distribution as most productive under R&D alliances and perfect IPR since they best concentrate scarce resources in discovering different knowledge combinations. In contrast, under collective invention and imperfect IPR, clustered networks better diffuse valuable ideas and knowledge resulting in the overall superior performance. Furthermore, under imperfect IPR, collective invention raises the inequality in payoffs among agents in networks with skewed degree distribution but reduces it for clustered topologies. The latter brings a novel explanation on why industries in the past have experienced a shift in the dominant pattern of knowledge exchange.

Dickinson’s Prosodic Music and the Songs on Death in Hamlet

This essay argues that the language of Hamlet emboldened Dickinson to develop her prosodic music. The essay’s argument unfolds in three steps. The first step instances Dickinson’s prosodic music by reading the poem draft “When what they sung for is undone” (Fr1545A, M 630). This step finds Dickinson’s prosodic music arise in distinctive word arrangements that show three features: interlaced phonic echoes, the rhythms of short-lined verse where rhyme marks stanzas, and the motions of intonation. The essay’s second step interprets the evidence of Shakespeare’s influence in the one poem where Dickinson named not only Shakespeare, but also Hamlet, Romeo, and Juliet, “Drama’s Vitallest Expression is the Common Day” (Fr776, M 381). A new reading of this poem shows that Shakespeare inspired Dickinson to develop her lyric art. The essay’s third step pursues the copious evidence of Shakespeare’s influence elsewhere in Dickinson’s writing. This step explicates categories of reference to Shakespeare and to Hamlet, focuses on the songs on death in the play, and interleaves in its discussion of these songs the reading of two Dickinson poems on death, “All overgrown by cunning moss” (Fr146, M 86) and “Praise it - ’tis dead - ” (Fr1406, M 595). Prosodic and thematic ties relate the songs in Hamlet to these poems and show that Dickinson’s lyric art is more inventively resonant in her own distinctive arrangements of words.

Human Olfaction at the Intersection of Language, Culture, and Biology

The human sense of smell can accomplish astonishing feats, yet there remains a prevailing belief that olfactory language is deficient. Numerous studies with English speakers support this view: there are few terms for odors, odor talk is infrequent, and naming odors is difficult. However, this is not true across the world. Many languages have sizeable smell lexicons - smell is even grammaticalized. In addition, for some cultures smell talk is more frequent and odor naming easier. This linguistic variation is as yet unexplained but could be the result of ecological, cultural, or genetic factors or a combination thereof. Different ways of talking about smells may shape aspects of olfactory cognition too. Critically, this variation sheds new light on this important sensory modality.

Compound words on the Jakarta post newspaper and Việtnam news newspaper

A newspaper has become the major news source around the world, either the printed or online newspaper. A newspaper provides many kinds of news and from different perspectives. Words in the newspaper play a significant role to deliver the information to the readers. The morpho-semantic study is needed to find out the uncommon words and their meaning in the newspaper. News in The Jakarta Post newspaper and Việt Nam News newspaper were analyzed, applying Hamawand’s (2001) compound categorization. Endocentric compound and exocentric compound by O’Grady et al (2016) are also being used in this study. The data were taken in a purposive sampling technique by observing eight news in the business column by The Jakarta Post and nine news in the economy column by Việt Nam News, taken from August 28, 2020, until September 4, 2020. Both newspapers contain distinctive compound words related to the economy that is still rarely known by people. From the total seventeen news, only a noun compound and adjective compound are found in the news, while the verb compound does not appear at all. The total of compound words found in the news is 25; there are 18 noun compounds and 7 adjective compounds found in the news. There are 16 endocentric compounds and 9 exocentric compounds found. The result shows that noun compounds and endocentric compounds appear more often than adjective compounds and exocentric compounds.

A Study on the Constitution and Structural Properties of Collocation in Russian

Many linguists have proposed various definition and properties of collocations, but there are no unified criteria for the classification of collocations. Sinclair(1996;1998:1999)’s definition of collocation is considered universal, and therefore has applied to not only English but many other languages. Following his theory, many linguists have attempted to treat collocations according to the statistical methods. On the other hand, many linguistics who support machine translation followed to treat collocation by Lexical Function that devised Melcu’k(1980;2007). However, formal and abstract criterions excluding lexical semantics can’t describe systematically all types of collocations. Each word in utterance has a distinctive word that semantically related to extralinguistic situation and reality. E. Coseriu, V. Vinogradov, and N. Arutyunova suggest the relation between word and reality. Through this process, V. Gak claimed the semantic agreement between words in utterance. From this point of view, this article examines some types of collocations and clarify for the constitution and semantic basic properties of collocations. Collocations are formed through word combination rule. In additions, semantic similar collocations make semantic syntagmatic types. Lexical close syntagmatic relations are classified of semantic type. According to this idea, this article shows analysis of collocation of adjective тёмный, using Russian dictionary and corpus.

Prophets and Prophecy in the Ancient Near East

Prophets and Prophecy in the Ancient Near East

Identifying influencers on social media

Abstract The increased availability of social media big data has created a unique challenge for marketing decision-makers; turning this data into useful information. One of the significant areas of opportunity in digital marketing is influencer marketing, but identifying these influencers from big data sets is a continual challenge. This research illustrates how one type of influencer, the market maven, can be identified using big data. Using a mixed-method combination of both self-report survey data and publicly accessible big data, we gathered 556,150 tweets from 370 active Twitter users. We then proposed and tested a range of social-media-based metrics to identify market mavens. Findings show that market mavens (when compared to non-mavens) have more followers, post more often, have less readable posts, use more uppercase letters, use less distinct words, and use hashtags more often. These metrics are openly available from public Twitter accounts and could integrate into a broad-scale decision support system for marketing and information systems managers. These findings have the potential to improve influencer identification effectiveness and efficiency, and thus improve influencer marketing.

A novel statistical mechanics-based metric for characterization of text documents

Machine learning (ML) uses intelligence-based statistical models to resolve characterization problems. However, the accuracy of ML models decreases as the volume of data increases since they are not able to capture the diversity and important regularities accompanying the huge volume. In this regard, the statistical mechanics’ (SM) paradigm for ML models must be investigated. SM like Big Data also deals with a large volume of instances. A correlation principle is proposed between data represented as words in a text corpus and a large volume of particles within a system. Based on it a new similarity measure, namely degeneracy-based statistical similarity measure (DSSM) is proposed. The DSSM is directly proportional to the ratio of the total energy of two documents with maximally similar words and the total number of distinct words in the document. The DSSM showed higher performance with regards to existing measures such as Euclidean, Cosine, SMTP, and MBSM.

Morphological processing in the flankers task

ABSTRACT Does the processing of words with a transparent morphological structure benefit from this structure? Here we show that the flankers task provides an interesting novel angle on this well-researched issue. Participants saw transparent suffixed target words flanked by their stem (e.g. farm farmer farm), as well as pseudo-suffixed words and non-suffixed words flanked by their embedded word (e.g. corn corner corn; cash cashew cash). Targets were also tested with unrelated word flankers (e.g. book farmer book), and participants made lexical decisions to the central targets. We predicted that truly suffixed word identification would be facilitated by the presence of stem flankers over and above any purely orthographic effects that were expected to be revealed in the pseudo-morphological and non-morphological conditions. We found exactly that pattern and conclude that parallel processing of distinct word identities in the flankers task is modulated by the transparent morphological relations between these words.

Joint string complexity for Markov sources: Small data matters

String complexity is defined as the cardinality of a set of all distinct words (factors) of a given string. For two strings, we introduce the joint string complexity as the cardinality of a set of words that are common to both strings. String complexity finds a number of applications from capturing the richness of a language to finding similarities between two genome sequences. In this paper we analyze the joint string complexity when both strings are generated by Markov sources. We prove that the joint string complexity grows linearly (in terms of the string lengths) when both sources are statistically indistinguishable and sublinearly when sources are statistically distinguishable. Precise analysis of the joint string complexity requires subtle singularity analysis and saddle point method over infinity many saddle points leading to novel oscillatory phenomena with single and double periodicities. To overcome these challenges, we apply analytic techniques such as multivariate generating functions, multivariate depoissonization and Mellin transform, spectral matrix analysis, and complex asymptotic methods.