Context

This dataset contains 20k news headlines, descriptions & articles from August 11, 2019 to June 8, 2020 obtained from Indian Express.

Acknowledgements

This dataset was obtained from www.indianexpress.com

Content

article_id: has generated article id's. headline: headline of the article. desc: description of the article date: date and time of the article url: url of the article articles: full article article_type: short, mid, long values to show the length of the article. article_length: ength of the article.

Medium Articles dataset

Medium is an American online publishing platform launched in August 2012. Crawl Feeds team extracted data from medium articles for research and analysis purposes.

Fields

Total fields: 15

url, crawled_at, id, title, author, published_at, author_url, reading_time, total_claps, raw_description, source, description, tags, images, modified_at

Get complete dataset from crawl feeds over more than 500K+ records Link

By downloading the data, you agree with the terms & conditions mentioned below:

Data Access: The data in the research collection may only be used for research purposes. Portions of the data are copyrighted and have commercial value as data, so you must be careful to use them only for research purposes.

Summaries, analyses and interpretations of the linguistic properties of the information may be derived and published, provided it is impossible to reconstruct the information from these summaries. You may not try identifying the individuals whose texts are included in this dataset. You may not try to identify the original entry on the fact-checking site. You are not permitted to publish any portion of the dataset besides summary statistics or share it with anyone else.

We grant you the right to access the collection's content as described in this agreement. You may not otherwise make unauthorised commercial use of, reproduce, prepare derivative works, distribute copies, perform, or publicly display the collection or parts of it. You are responsible for keeping and storing the data in a way that others cannot access. The data is provided free of charge.

Citation

Please cite our work as

@InProceedings{clef-checkthat:2022:task3, author = {K{"o}hler, Juliane and Shahi, Gautam Kishore and Stru{\ss}, Julia Maria and Wiegand, Michael and Siegel, Melanie and Mandl, Thomas}, title = "Overview of the {CLEF}-2022 {CheckThat}! Lab Task 3 on Fake News Detection", year = {2022}, booktitle = "Working Notes of CLEF 2022---Conference and Labs of the Evaluation Forum", series = {CLEF~'2022}, address = {Bologna, Italy},}

@article{shahi2021overview, title={Overview of the CLEF-2021 CheckThat! lab task 3 on fake news detection}, author={Shahi, Gautam Kishore and Stru{\ss}, Julia Maria and Mandl, Thomas}, journal={Working Notes of CLEF}, year={2021} }

Problem Definition: Given the text of a news article, determine whether the main claim made in the article is true, partially true, false, or other (e.g., claims in dispute) and detect the topical domain of the article. This task will run in English and German.

Task 3: Multi-class fake news detection of news articles (English) Sub-task A would detect fake news designed as a four-class classification problem. Given the text of a news article, determine whether the main claim made in the article is true, partially true, false, or other. The training data will be released in batches and roughly about 1264 articles with the respective label in English language. Our definitions for the categories are as follows:

False - The main claim made in an article is untrue.

Partially False - The main claim of an article is a mixture of true and false information. The article contains partially true and partially false information but cannot be considered 100% true. It includes all articles in categories like partially false, partially true, mostly true, miscaptioned, misleading etc., as defined by different fact-checking services.

True - This rating indicates that the primary elements of the main claim are demonstrably true.

Other- An article that cannot be categorised as true, false, or partially false due to a lack of evidence about its claims. This category includes articles in dispute and unproven articles.

Cross-Lingual Task (German)

Along with the multi-class task for the English language, we have introduced a task for low-resourced language. We will provide the data for the test in the German language. The idea of the task is to use the English data and the concept of transfer to build a classification model for the German language.

Input Data

The data will be provided in the format of Id, title, text, rating, the domain; the description of the columns is as follows:

ID- Unique identifier of the news article

Title- Title of the news article

text- Text mentioned inside the news article

our rating - class of the news article as false, partially false, true, other

Output data format

public_id- Unique identifier of the news article

predicted_rating- predicted class

Sample File

public_id, predicted_rating 1, false 2, true

IMPORTANT!

We have used the data from 2010 to 2022, and the content of fake news is mixed up with several topics like elections, COVID-19 etc.

Baseline: For this task, we have created a baseline system. The baseline system can be found at https://zenodo.org/record/6362498

Related Work

Shahi GK. AMUSED: An Annotation Framework of Multi-modal Social Media Data. arXiv preprint arXiv:2010.00502. 2020 Oct 1.https://arxiv.org/pdf/2010.00502.pdf

G. K. Shahi and D. Nandini, “FakeCovid – a multilingual cross-domain fact check news dataset for covid-19,” in workshop Proceedings of the 14th International AAAI Conference on Web and Social Media, 2020. http://workshop-proceedings.icwsm.org/abstract?id=2020_14

Shahi, G. K., Dirkson, A., & Majchrzak, T. A. (2021). An exploratory study of covid-19 misinformation on twitter. Online Social Networks and Media, 22, 100104. doi: 10.1016/j.osnem.2020.100104

Shahi, G. K., Struß, J. M., & Mandl, T. (2021). Overview of the CLEF-2021 CheckThat! lab task 3 on fake news detection. Working Notes of CLEF.

Nakov, P., Da San Martino, G., Elsayed, T., Barrón-Cedeno, A., Míguez, R., Shaar, S., ... & Mandl, T. (2021, March). The CLEF-2021 CheckThat! lab on detecting check-worthy claims, previously fact-checked claims, and fake news. In European Conference on Information Retrieval (pp. 639-649). Springer, Cham.

Nakov, P., Da San Martino, G., Elsayed, T., Barrón-Cedeño, A., Míguez, R., Shaar, S., ... & Kartal, Y. S. (2021, September). Overview of the CLEF–2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake News. In International Conference of the Cross-Language Evaluation Forum for European Languages (pp. 264-291). Springer, Cham.

This study estimates the effect of data sharing on the citations of academic articles, using journal policies as a natural experiment. We begin by examining 17 high-impact journals that have adopted the requirement that data from published articles be publicly posted. We match these 17 journals to 13 journals without policy changes and find that empirical articles published just before their change in editorial policy have citation rates with no statistically significant difference from those published shortly after the shift. We then ask whether this null result stems from poor compliance with data sharing policies, and use the data sharing policy changes as instrumental variables to examine more closely two leading journals in economics and political science with relatively strong enforcement of new data policies. We find that articles that make their data available receive 97 additional citations (estimate standard error of 34). We conclude that: a) authors who share data may be rewarded eventually with additional scholarly citations, and b) data-posting policies alone do not increase the impact of articles published in a journal unless those policies are enforced.

PubMed Central® (PMC) is a free full-text archive of biomedical and life sciences journal article at the U.S. National Institutes of Health's National Library of Medicine (NIH/NLM). The PubMed Central (PMC) Article Datasets include full-text articles archived in PMC and made available under license terms that allow for text mining and other types of secondary analysis and reuse. The articles are organized on AWS based on general license type:

The PMC Open Access (OA) Subset, which includes all articles in PMC with a machine-readable Creative Commons license

The Author Manuscript Dataset, which includes all articles collected under a funder policy in PMC and made available in machine-readable formats for text mining

These datasets collectively span more than half of PMC’s total collection of full-text articles. PMC enables access to these datasets to expand the impact of open access and publicly-funded research; enable greater machine learning across the spectrum of scientific research; reach new audiences; and open new doors for discovery. The bucket in this registry contains individual articles in NISO Z39.96-2015 JATS XML format as well as in plain text as extracted from the XML. The bucket is updated daily with new and updated articles. Also included are file lists that include metadata for articles in each dataset.

The data used in this article is provided in S1 Data.

This dataset includes google scholar articles listing on data mining, this is very helpful in many educational research works. This dataset contains 936 unique entries. including title, description, author names, article link, cited by and related articles.

This dataset provides geospatial location data and scripts used to analyze the relationship between MODIS-derived NDVI and solar and sensor angles in a pinyon-juniper ecosystem in Grand Canyon National Park. The data are provided in support of the following publication: "Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States". The data and scripts allow users to replicate, test, or further explore results. The file GrcaScpnModisCellCenters.csv contains locations (latitude-longitude) of all the 250-m MODIS (MOD09GQ) cell centers associated with the Grand Canyon pinyon-juniper ecosystem that the Southern Colorado Plateau Network (SCPN) is monitoring through its land surface phenology and integrated upland monitoring programs. The file SolarSensorAngles.csv contains MODIS angle measurements for the pixel at the phenocam location plus a random 100 point subset of pixels within the GRCA-PJ ecosystem. The script files (folder: 'Code') consist of 1) a Google Earth Engine (GEE) script used to download MODIS data through the GEE javascript interface, and 2) a script used to calculate derived variables and to test relationships between solar and sensor angles and NDVI using the statistical software package 'R'. The file Fig_8_NdviSolarSensor.JPG shows NDVI dependence on solar and sensor geometry demonstrated for both a single pixel/year and for multiple pixels over time. (Left) MODIS NDVI versus solar-to-sensor angle for the Grand Canyon phenocam location in 2018, the year for which there is corresponding phenocam data. (Right) Modeled r-squared values by year for 100 randomly selected MODIS pixels in the SCPN-monitored Grand Canyon pinyon-juniper ecosystem. The model for forward-scatter MODIS-NDVI is log(NDVI) ~ solar-to-sensor angle. The model for back-scatter MODIS-NDVI is log(NDVI) ~ solar-to-sensor angle + sensor zenith angle. Boxplots show interquartile ranges; whiskers extend to 10th and 90th percentiles. The horizontal line marking the average median value for forward-scatter r-squared (0.835) is nearly indistinguishable from the back-scatter line (0.833). The dataset folder also includes supplemental R-project and packrat files that allow the user to apply the workflow by opening a project that will use the same package versions used in this study (eg, .folders Rproj.user, and packrat, and files .RData, and PhenocamPR.Rproj). The empty folder GEE_DataAngles is included so that the user can save the data files from the Google Earth Engine scripts to this location, where they can then be incorporated into the r-processing scripts without needing to change folder names. To successfully use the packrat information to replicate the exact processing steps that were used, the user should refer to packrat documentation available at https://cran.r-project.org/web/packages/packrat/index.html and at https://www.rdocumentation.org/packages/packrat/versions/0.5.0. Alternatively, the user may also use the descriptive documentation phenopix package documentation, and description/references provided in the associated journal article to process the data to achieve the same results using newer packages or other software programs.

Background Disruption of the balance between apoptosis and proliferation is considered to be an important factor in the development and progression of tumours. In the present study we determined the in vivo cell kinetics along the spectrum of apparently normal epithelium, hyperplasia, preinvasive lesions and invasive carcinoma, in breast tissues affected by fibrocystic changes in which preinvasive and/or invasive lesions developed, as a model of breast carcinogenesis. Materials and methods A total of 32 areas of apparently normal epithelium and 135 ductal proliferative and neoplastic lesions were studied. More than one epithelial lesion per case were analyzed. The apoptotic index (AI) and the proliferative index (PI) were expressed as the percentage of TdT-mediated dUTP-nick end-labelling (TUNEL) and Ki-67-positive cells, respectively. The PI/AI (P/A index) was calculated for each case. Results The AIs and PIs were significantly higher in hyperplasia than in apparently normal epithelium (P = 0.04 and P = 0.0005, respectively), in atypical hyperplasia than in hyperplasia (P = 0.01 and P = 0.04, respectively) and in invasive carcinoma than in in situ carcinoma (P < 0.001 and P < 0.001, respectively). The two indices were similar in atypical hyperplasia and in in situ carcinoma. The P/A index increased significantly from normal epithelium to hyperplasia (P = 0.01) and from preinvasive lesions to invasive carcinoma (P = 0.04) whereas it was decreased (non-significantly) from hyperplasia to preinvasive lesions. A strong positive correlation between the AIs and the PIs was found (r = 0.83, P < 0.001). Conclusion These findings suggest accelerating cell turnover along the continuum of breast carcinogenesis. Atypical hyperplasias and in situ carcinomas might be kinetically similar lesions. In the transition from normal epithelium to hyperplasia and from preinvasive lesions to invasive carcinoma the net growth of epithelial cells results from a growth imbalance in favour of proliferation. In the transition from hyperplasia to preinvasive lesions there is an imbalance in favour of apoptosis.

List of Top Authors of Journal of Big Data sorted by article citations.

ABSTRACT Context: this document is designed to be along with those that are in the first edition of the new section of the Journal of Contemporary Administration (RAC): the tutorial-articles section. Objective: the purpose is to present the new section and discuss relevant topics of tutorial-articles. Method: I divide the document into three main parts. First, I provide a summary of the state of the art in open data and open code at the current date that, jointly, create the context for tutorial-articles. Second, I provide some guidance to the future of the section on tutorial-articles, providing a structure and some insights that can be developed in the future. Third, I offer a short R script to show examples of open data that, I believe, can be used in the future in tutorial-articles, but also in innovative empirical studies. Conclusion: finally, I provide a short description of the first tutorial-articles accepted for publication in this current RAC’s edition.

Mathematics article counts, 2014.

Data set to support the Bjork and Solomon study "Developing an effective market for OA APC"

The supplementary material includes the original and reduced spectrum auction BPMN models, the original and the reduced spectrum auction Petri Nets, and the verification results for Article "Reduction of Data-Value-Aware Process Models based on Relevance".

Nearing, J. T. et al. Microbiome differential abundance methods produce different results across 38 datasets. Nat Commun 13, 342, doi:10.1038/s41467-022-28034-z (2022).
https://www.nature.com/articles/s41467-022-28034-z
Exercises that can be used to reproduce pictures of articles.

This report tracks the name and source/website of the articles referenced for each month shown. Titles with a department name at the end reflect information provided from the department website. The other articles are maintained by SF311 to supplement department data. Articles used by 311 in the course of creating service requests (such as graffiti handling processes) are not included. Metrics of knowledge use from September and October 2017 was inconsistent following the migration to a new system in September 2017. Additionally, the names of articles is different than article names prior to the upgrade. This dataset is updated monthly. Note - This is not up-to-date as of June 2023. We are working to fully load the full data in the near future. For historical data (Top Articles Referenced through Aug. 2017), go to: https://data.sfgov.org/City-Infrastructure/311-Top-Articles-Referenced-historical-through-Aug/hrr4-hjc6/data

This dataset provides supporting information for figures in the journal article entitled: Mutagenicity- and Pollutant-Emission Factors of Pellet-Fueled Gasifier Cookstoves: Comparison with Other Combustion Sources. This dataset is associated with the following publication: Champion, W., S. Warren, I. Kooter, W. Preston, T. Krantz, D. DeMarini, and J. Jetter. Mutagenicity- and Pollutant-Emission Factors of Pellet-Fueled Gasifier Cookstoves: Comparison with Other Combustion Sources. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 739(October 15 2020): 139488, (2020).

Reservoir operation rules(1) continuous flood discharge with ecological priority(2) pulse flood discharge with ecological priority
(3) pulse flood discharge with equal weight of ecology and power generation(4) pulse flood discharge with power generation priority

Western-blotting Data for Lactiplantibacillus plantarum EP21

This dataset supports the following publication: "Solar and sensor geometry, not vegetation response, drive satellite NDVI phenology in widespread ecosystems of the western United States" (DOI:10.1016/j.rse.2020.112013). The data release allows users to replicate, test, or further explore results. The dataset consists of 4 separate items based on the analysis approach used in the original publication 1) the 'Phenocam' dataset uses images from a phenocam in a pinyon juniper ecosystem in Grand Canyon National Park to determine phenological patterns of multiple plant species. The 'Phenocam' dataset consists of scripts and tabular data developed while performing analyses and includes the final NDVI values for all areas of interest (AOIs) described in the associated publication. 2) the 'SolarSensorAnalysis' dataset uses downloaded tabular MODIS data to explore relationships between NDVI and multiple solar and sensor angles. The 'SolarSensorAnalysis' dataset consists of download and analysis scripts in Google Earth Engine and R. The source MODIS data used in the analysis are too large to include but are provided through MODIS providers and can be accessed through Google Earth Engine using the included script. A csv file includes solar and sensor angle information for the MODIS pixel closest to the phenocam as well as for a sample of 100 randomly selected MODIS pixels within the GRCA-PJ ecosystem. 3) the 'WinterPeakExtent' dataset includes final geotiffs showing the temporal frequency extent and associated vegetation physiognomic types experiencing winter NDVI peaks in the western US. 4) the "SensorComparison" dataset contains the NDVI time series at the phenocam location from 4 other satellites as well as the code used to download these data.