dataesr/scientific-paragraphs-categorization huggingface dataset:
Differential expression analysis, MDS plots, and filtering The DEG analysis was performed in R v3. 6. 3 (72)  with package edgeR v. 3. 24. 3 (73). To reduce the problem associated with multiple testing in the DEG calculation phase, we removed all genes not represented by enough reads (unexpressed genes). For this reason, we retain only those genes that are represented by at least 1 cpm (counts per million) reads in at least three samples. Gene expression at each of the three time points of the cross samples (T1, T2, and T3) was compared with gene expression in MT+ and MT-at T2 generating six different datasets: cross T1 versus MT+, cross T1 versus MT-, cross T2 versus MT+, cross T2 versus MT-, cross T3 versus MT+, and cross T3 versus MT-. Data were then normalized in edgeR to scale the raw library sizes.
To assess the overall similarity between samples, we performed an MDS analysis through the edgeR plotMDS function on raw counts and plotted samples on a two-dimensional scatterplot; thus, the distances on the plot approximate the expression differences between the samples. The method used for testing DEGs was the exact test. Because there could be differences in terms of gene expression between MT+ and MT-, to avoid the bias resulting from DEGs showing an MT-specific pattern of expression, we decided to discard those genes whose expression change was discordant between MT+ and MT-in each of the comparisons. That is, for each time point, we selected only those genes resulting significantly up-or down-regulated (logFC ≥ 1 or ≤ -1 and FDR ≤ 0. 05) in both the comparisons with MT+ and MT-. P. multistriata gene models and RNA-seq data can be visualized in the genome browser at http://bioinfo.
Venn diagrams and hierarchical clustering Venn diagrams were plotted in R using the package Venn v1. 9. The expression levels of the DEGs were plotted as pseudocounts [log 2 (raw_counts + 1)], or counts per million, on a row scaled heatmap obtained in R with the package ComplexHeatmap v. 2. 6. 2  (74). The hierarchical clustering was performed within the Complex-Heatmap function (cluster_columns = TRUE, clustering_distance_ columns = "pearson"). Heatmaps in Figs. 2  and 3  were realized using the mean of the log 2 FCs in cross samples compared to MT+ and MT-monocultures using the conditional formatting tool in Excel.
The different cell types (gametes/zygotes, auxospores, and F1 cells) were distinguished from the parental cells on the basis of their shape (see representative pictures in figs. S3 and S4) and imaged one by one with a subcellular resolution (pixel size, 1. 7 mm 2 ). Photosynthetic parameters were measured at multiple time points during the cross experiment, and all data relative to individual measurements of the same stages in the two crosses were averaged, with the exception of parental cells in the cross sample at the last time point (after 72 hours, which is the time when arrested parental cells in the cross resume growth) that were calculated separately. Chlorophyll fluorescence was imaged with an optical microscope (CKX 53 Olympus, Japan) equipped with an imaging system (JBeamBio, France).
Acknowledgments: We thank  I. Scheuring  and  T. Wyatt  for discussions on the evolutionary implications of our results,  A. Passarelli  [Monitoring and Environmental Data (MEDA) unit, SZN] for nutrient measurements, the  Molecular Biology and Sequencing service (SBM)  for RNA quality assessments, the  BIOINforMA (Bioinformatics for Marine Biology ) service for assistance in bioinformatics analyses, and the  EMBL GeneCore service  for RNA sequencing.
Funding: This work was supported by the  Italian Flagship Program RITMARE  and the  Gordon and Betty Moore Foundation  through grant no. 7978  to M. I. F. G. F. received funds from GRAL, a program from the  Chemistry Biology Health (CBH) Graduate School of University Grenoble Alpes  ( ANR-17-EURE-0003 ), and from the  European Research Council: ERC ChloroMito  (grant no. 833184 ). M. V. and K. S. were supported by a PhD fellowship funded by the  Open University-SZN  PhD program. Author contributions: M. I. F. , M. M. , D. I. , M. R. d. A. , and R. A. designed the study. R. A. , P. M. , and G. F. performed the experiments. K. S. and.
Mass media plays an important role in the construction and circulation of risk perception associated with animals. Widely feared groups such as spiders frequently end up in the spotlight of traditional and social media. We compiled an expert-curated global database on the online newspaper coverage of human-spider encounters over the past ten years (2010-2020). This database includes information about the location of each human-spider encounter reported in the news article and a quantitative characterisation of the content-location, presence of photographs of spiders and bites, number and type of errors, consultation of experts, and a subjective assessment of sensationalism. In total, we collected 5348 unique news articles from 81 countries in 40 languages. The database refers to 211 identified and unidentified spider species and 2644 unique human-spider encounters (1121 bites and 147 as deadly bites).
Intending to fill this gap, here we compiled an expert-curated global database on the coverage of human-spider encounters in online newspaper media and their accuracy and reliability over the past ten years (2010-2020) (Fig. 1 ). This database includes detailed information about the location of each human-spider encounter reported by the media, year of publication, and a quantitative characterisation of the content of each piece of news (presence of photographs of spiders and bites, number and type of errors, whether experts were consulted, and whether the content is sensationalistic or neutral). With this database, we hope to stimulate further research on the human dimension of spiders and their representation in the media.
Methods Geographical coverage of the database. We aimed to compile a comprehensive database of global coverage of countries, languages and online newspapers. To this end, we put together a large network of spider experts to mine data in as many languages and countries as possible. We searched for news in 40 unique languages and covered the online press in 81 countries and all six continents where spiders can be found. Due to an uneven availability of experts, however, there is a bias in the database towards temperate regions (Europe and North America). African countries are the least represented. temporal coverage of the database. We focused on newspaper articles published online between 2010 and 2020 (partial and uneven temporal coverage for 2020). Thus, the temporal span of our study mostly covered the advent of online journalism and the parallel diffusion of news through social media platforms  29.
For each country and language, we carried out online searches in different languages with Google News (Appendix S1 -Figure  S1 ), choosing multiple keyword combinations and the years between 2010 and Fig. 1  The potential of news articles as a source of data. This database offers a quantitative baseline to pursue research on the human-dimensions of spiders and their representation in the media. This research may include answering questions related to the cultural component of spider conservation, evaluation of people's perceptions of spiders via opinion mining techniques, and generation of ecological insights, among others. Original illustration by Jagoba Malumbres-Olarte. 2020-this can be specified using the 'Custom range' tool in Google News (Appendix S1 -Figure  S2 ). Note that for a few countries that were not available in Google News at the time of the search, such as Finland, Denmark, or Botswana, we performed searches directly in Google.
Then, we read the full article and scored the g) spider species identity based on the description in the news article, even if the attribution was incorrect based on our expert opinion. We reported species identity to the lowest taxonomic level possible based on the information in the article (typically species or genus level, but sometimes only family level). If the species identification was not provided in the article but it was possible to infer (e. g. , referring to a species being identifiable from a picture or a report of a "widow spider" identifiable to species based on geography), we reported this identification in the database. To achieve standardization throughout the database, we converted all names to the closest valid scientific name, based on the most updated spider taxonomy  31.
Sensationalism in animal-related news articles is often associated with emotional words, expressions, and images  2, 25, 26. Examples of titles of sensationalistic versus non-sensationalistic news articles focusing on the same event are: "Thousands of spiders 'bleed out of the walls' and force family from home" vs. "Home Infested With Brown Recluse Spiders in Missouri". Throughout the database, frequent words associated with sensationalistic content were 'alarm' , 'agony' , 'attack' , 'boom' , 'deadly' , 'creepy crawly' , 'devil' , 'fear' , 'hell' , 'killer' , 'murderer' , 'nasty' , 'nightmare' , 'panic' , 'terrible' , 'terrifying' , and 'terror' 2 , as well as magnifying adjectives that exaggerated any features of the encounter (e. g. , body size  [34] [35] [36]  , hairiness  35  ). However, the presence of one of these words did not necessarily result in an article being scored as sensationalistic.
Data records Database availability. The database is freely available in Figshare  37. The database is provided both as a tab-delimited file (. csv) and as an excel file (. xslx). Description of columns is in Table  1  but also in the metadata file uploaded alongside the database in Figshare. Code to access the database in R environment  38  and derive basic summary statistics and graphs shown in this paper is available in GitHub (see section "Code Availability"). Description of the database. In total, we collected 5348 unique news articles from 81 countries in 40 languages. The database has an uneven temporal coverage, with most news articles concentrating in recent years (Fig. 2a ). There is also a seasonal pattern in the distribution of news articles. In the northern hemisphere, most news articles occur throughout the summer season (Fig.
2b ), whereas the pattern is less clear in the south (Fig. 2c ). The number of news items by countries varies by at least three orders of magnitude, from hundreds (United Kingdom: 865; United States: 537; Italy: 412; Russia: 395; France: 319) to a handful of news articles, or none (Table  2 ). The database includes 6204 reports of human-spider encounters (corresponding to 2644 unique events) and 211 identified and unidentified spider species-note that a single news article may report about multiple human-spider encounters. Of these unique events, 1121 were reported by the news articles as bites, and 147 as deadly bites (Fig. 3a ). The majority of reported encounters is concentrated at northern latitudes in the northern hemisphere (median latitude = 46. 9°), whereas the median latitude of reported bites and deadly bites is further south (41.
Language (Country) Expert in charge Details Basque (France, Spain) Jagoba Malumbres-Olarte No news article was found, both using Google or by searching directly the websites of the few newspapers in Basque. English and Setswana (Botswana) Tharina L. Bird; Naledi T. Gonnye No news article was found, both using Google or by searching directly the websites of the local newspapers (n = 9). The lack of news was further confirmed by phone (see main text).
Marija Miličić No news article was found for Montenegro with direct search in Google and Google News. Table  2. Countries and languages for which no spider-related news articles were found. errors is variable (data not shown). Also, 43% of news articles were assessed by experts as sensationalistic; the frequency of sensationalistic versus non-sensationalistic news varied substantially by continent (Fig. 4d ). even zeros matter. For a few countries, we found no online news articles reporting human-spider encounters (Table  2 ). An informative case is Botswana, where the authors in charge performed an in-depth investigation to explain the lack of relevant results. Since Google News does not work for Botswana, they carried out the initial search in Google, which yielded no relevant results using any combination of keywords.
technical validation Data accuracy and curation. To increase the accuracy and internal consistency of our database, and given subjectivity in the assignment of certain values (e. g. , sensationalism, errors), we re-assessed news for most articles in English (N = 1719; 80%) and some of the other most common languages based on the availability of native speakers (French, 53%; Italian, 88%; Spanish, 48%). The column "Quality_check" in the database indicates whether this re-assessment was performed for a given article. We assigned a pair of authors to a subset of these language-based datasets so they could independently re-examine and score articles that were previously mined by the original contributor. The re-assessors scored the articles in the same manner as described previously (see section "Extraction of information for each media report") and compared their individual datasets with each other.
Discrepancies in scores were discussed and compared with the original dataset to reach a consensus on final scores. We estimated the rate of agreement between two re-assessors via Cohen's kappa statistic  40  , calculated for all the scores of variables that may imply a degree of subjectivity in the assessment. We derived the confidence intervals using variance estimate  41. We carried out this analysis only on English news (Table  3 ). Limitations in using the database. Users of the database must be aware of the following limitations: i) The data collected here refer to online journalism only. The database does not cover the representation of spiders in the printed versions of traditional newspapers; ii) Because Google's search algorithm varies by country and user, the relationship between the number of published news articles and the number of results returned is likely not consistent.
For example, the total number of news articles in China is unreliable due to the restrictions imposed by the government on Google. Consequently, we recommend against comparing absolute numbers of news items across countries, but rather always using relative numbers (e. g. , proportion of errors, proportion of spider bites versus encounters, relative frequency of a given species in the press); and iii) Likewise, any temporal trend must be interpreted with caution because news publishers can occasionally remove pieces of news from the Google News index or simply delete old news. The probability of this happening increases with time and thus may be partly responsible for the apparent increase in the volume of news articles over time in this database (Fig. 2a ).
Usage Notes This database allows users to investigate questions related to the social dimension of spiders and the psychology of arachnophobia, but also contemporary problems in ecology  42, 43  and conservation biology  44. To stimulate the use of the database, we discuss what we believe are some important avenues of research-while being aware that many other questions and patterns await to be explored  45. Note that some of these research questions have already been briefly introduced in Mammola et al. (ref. 2  ), but here are expanded on and contextualized within the framework of a global-scale database. comparison among countries and through time. Some of the first questions that come to mind are about the reasons underlying the disparity in the quality of news across regions and countries  2  , namely what are the main ecological, cultural, and/or social factors that explain the observed patterns? This dataset could be used to test the hypothesis that socio-economic factors, demographic features, level of education or literacy and/ or cultural values affect the quality and taxonomic bias of spider-related news in a given country.
Linguistic analysis. The title of each news article and other bodies of texts that can be automatically extracted using the URL of each news item (e. g. , comments on the online article, comments in response to the shares of the article on social media) offer a large source of data in the domain of Sentiment Analysis or Opinion Mining-defined as the computational study of people's emotions and attitudes toward a given topic 51. A very simple example is provided in Fig. 5 , where we used R text mining tools  52  to compare the usage of words in sensationalistic versus non-sensationalistic titles of articles written in English. Inevitably, these kinds of analyses are more easily performed on news published in English because of the larger sample size. Source of iecological knowledge. This database has the potential to generate ecological insights.
Similar applications broadly fall within the domain of iEcology, an emerging research field that "[…] seeks to quantify patterns and processes in the natural world using data accumulated in digital sources collected for other purposes"  42. The database of spider news provides data on > 200 spider species (Fig. 3d ); for most of these species, we have recorded the coordinates of the locality where the human-spider encounter supposedly took place. Some of these records are clearly wrong (i. e. , the species reported is not correct), but the presence of the supposedly encountered species could be verified by experts. In other words, the news reports could be used by experts (spider experts, in this case) to inspect areas where a given species may be present. Once a reliable database for a given species is cleaned, one could explore different ecological patterns.
In Italy, for example, the seasonal distribution of news articles on the Mediterranean black widow [Latrodectus tredecimguttatus (Rossi, 1790)] overlaps almost perfectly with the known phenology of the species  2. Similar phenological insights may be checked for other species. Also, recent niche modelling studies have shown that internet-derived distribution data can be useful for mapping the predicted distribution of spiders (reviewed in ref. 53  ), especially species that are easily identified in the field or by photos  [54] [55] [56] [57]. For some of the most abundant species in our database (e. g. , Loxosceles spp. and Latrodectus spp. ), it is possible to compare whether.
e. , the magnitude of polarity) and the diversity of text used to describe experiences (see methods). We hypothesised that questions framed to encourage people to think about their positive premenstrual experiences would diminish how negatively they would report their experiences and/or report some positive experiences. To test this hypothesis, we used an online survey to collect text data on the premenstrual experience (PME). Participants were randomly allocated to one of three conditions where they were asked to describe their premenstrual experience using a different framing. Some were asked about experiences in general without specifying the type of experience, and others were asked about positive and negative experiences with varying orders. We then used text analysis to investigate differences between polarity scores and word diversity across the groups.
There are no differences between treatments manipulating the order of questions. A total of 4,534 people participated in the study. After removing un nished responses and those that did not meet the inclusion criteria (menstrual bleed in the past three months; over 18), the nal sample size was 2,638 (Fig. 1 ). Participants were aged 18 to 54 (mean +/-sd = 28), born in 117 different countries, the majority in the UK (n = 713), America (n = 590), Australia (n = 248) and Canada (n = 113), though there were individuals from ve continents. Altogether, 17% used hormonal contraception (n = 458), this gure is in line with what we expected compared to the rate of hormonal contraceptive use worldwide (21. 5%  [39] ) (Table  1 ). The mean polarity of the data was - 0. 19 showing that all three groups had a negative score skew (Fig.
Discussion We investigated whether the premenstrual experience (PME) is in uenced by question framing using an online experiment. We manipulated the phrasing of the question asking for a description of the premenstrual experience (control: nothing speci ed; treatments: framing the question speci cally asking about both negative and positive experiences in a different order). Drawing on the analysis of text data collected, the results show that (1) in both control and treatment groups, PME was overall described negatively, (2) framing the question with emotional valence specifying both positive and negative experiences, resulted in higher odds of reporting neutral compared to negative responses, and (3) the experience was described less negatively, and the breadth of symptoms described was higher (more diverse) in treatments compared to the control group.
b) Survey The included a maximum of 21 questions depending on individual circumstances. The survey collected quantitative data on age, level of partner support, medication, country of birth, vitamin use, and contraceptive use, as well as qualitative data on the premenstrual experience through a free text entry question (SI 3). These data were collected as they have been shown to affect the symptoms and intensity of symptoms that menstruating individuals describe  [64] [65] [66] [67] [68] [69] [70] [71]. Data collection took place from the 13th March 2020 through to 1st July 2020 and was halted once no more push noti cations were scheduled, and no new responses had been recorded for three days.
e) Text Analysis Data Cleaning: Text processing was performed, as texts written in questionnaires are often unedited, typos and abbreviations often occur  [73]. Similarly, the same words can be represented differently, such as 'PMS', 'premenstrual syndrome' and 'pre-menstrual syndrome'. To address this, a cleaning function was created (the script is open access and can be found on GitHub (https://bit. ly/3saG0ie). The function created was adapted from code written in the 'textclean' package  [74].
i) Extracting the polarity of responses Polarity scores: Polarity scores were calculated to answer the following two questions: (i) do the number of positive, negative and neutral responses vary by group? (ii) does the range of scores vary by group? To create a polarity score for each response, we performed a sentiment analysis, a lexicon-based approach that uses text mining and computational linguistics using the sentimentr package  [75]. By comparing words in the text to a pre-de ned dictionary of words (lexicon), an algorithm assigns positive, negative and neutral tags to sentences. Negators, shifters and intensi ers (words such as "not" and "really") are accounted for in the nal polarity score  [76]. A challenge in sentiment analysis is the lack of datasets that have been used to train a model which can adapt to speci c domains  [77].
We are not aware of any annotated datasets about menstruation that could be used to train a model to accurately classify responses as positive or negative. As such, we adapted the default lexicon in the sentimentr package  [75]  by creating a custom dictionary, whereby the polarity of relevant words was edited (SI 4). Word Diversity: The text was analysed to answer the following three questions (i) which single words (unigrams) are the most frequent and important in each group? (ii) what are the similarities in words between control and treatments? (iii) Are unique words found in any of the groups? First, further data processing was performed by tokenising the text to break sentences into a one-word-per-row format. Highly common words that do not carry meaning such as "and", "thus" (stopwords) were removed (SI 5), and applied to the text, removing 22,997 words, leaving 32,111.