For 2 different world top ranking peer reviewed academic journals: all of the accepted and rejected submissions covers last 5 years searched on academic bibliographic databases to review the journal’s performance in terms of the papers that it receives and that it publishes.
The data collected used for comparing the citation performance of the accepted publications against the competitor journals and as well as compares the rejected publications citations performance if they have been published in somewhere else including higher ranking academic journals. The collected data is also used for checking for possible biasing of referees and editors.
Input: The details for Accepted and rejected manuscripts and submissions to the journal in last 10 years
Output:
The citations performance for published papers and comparisons with the peer/competitor journals' performance.
If the rejected submissions were published in somewhere else after being rejected by the journal
The detail data about author geographical location, seniority and gender
Performance metrics for referee recommendations predicting the performance of accepted and rejected papers
Performance metrics for editors' decisions based on referee recommendations
For a research on Property Market Analysis, data collected from 2 different property advertisement web sites of the UK.
For data collection all for sale and for rent residential property advertisements collected for a given post code (first part of the postcode only such as NW2).
The data collected for rent and for sale residential properties was used for creating a new Buy2Let profitabilty index that indicates the return of investment for a possible buy action on a particular property.
For an insurance data aggregator organisation we have created a web automation:
For a pool of legitimate 5000 participating people looking for one of the car insurance or home insurance
We automatically enter the details of these people to get quotes for insurance from 4 different insurance providers
Aggregate the collected insurance quote data for creating insurance market analytics
In an econometry research study examining the effects of daylight hours on traffic accidents; we contributed to the faster conclusion of the study and the more efficient data analysis by the research team by collecting new features such as:
the time difference between sunset and sunrise at the time of the accident,
the angle of incidence of the sun from the geographical data in 5-year accident reports
Input: Datetime of the accident, x-y coordinates of the accident, direction of the vehicle(s) of the accident (Data covers 5 years )
Output: Input + the time difference between sunset and sunrise + the angle of incidence of the sun
In a management and business research study examining the dynamics of the ad-hoc team building, motivation factors of ad-hoc teams, interactions between teams and team members on online platforms, Kaggle web site data collected for analysing the team and competition data:
Output:
Kaggle Users & Teams Data
Kaggle Competitions Data
Kaggle Datasets
Kaggle Competions
Kaggle Forums & Interactions
For a social research study, data collected from 30 different online newspapers' archives for last 5 years to examine the hate speech texts against some social minority groups.
Millions of web pages including news, columns searched and collected after filtering for hate speech words or statements.
For an econometry research study, the birth countries for 25.000 CEO's of Fortune 500 companies between the years 2000 - 2014.
Birth countries for the CEO's were searched from public web data datasources like automated google search, wikipedia, people and biography databases.
Input:
Company details like company name, company ticker.
CEO's details like fullname, gender, year of birth, years being CEO of the company
Some other support information
Output:
Birth countries of the CEO's
In a public management research study, UK Companies House data collected for all of the newly incorporated, active and dissolved companies to see the shareholder structure and director changes in terms of the nationality of the shareholders and directors in 3 years after Brexit vote in 2016.
The aim of the study is to see if the companies having non British people as a shareholder or director are doing some changes for not to lose their commercial benefits after Brexit.
The size of the collected data is around 5M company records and 15M company people records.
For an econometry research study we have collected tweets of the Fortune 500 Companies CEO's who have known Twitter accounts. The data goes back as much as possible to get all history of the accounts.
Collected data was used to create monthly word frequencies and trying to find correlation with the stock exchange price changes of the company for that particular month.
For an academic conference organisation, we have collected data from the academic conference hosting system which didn't have user interface for exporting the detail information about the proceedings, authors, authors' geo-locations, keywords, abstracts.
The collected data was used for visualising the diversity of the conference joiners, geo-locations, countries of the authors, top most touched subjects, terms and keywords.
For a Finance research study, data collected from Telegram Groups and Channels to do research on the organized fraud and manipulating bot accounts that are being used for trapping people by to make buy or sell actions.
The collected data was used in the research in terms of timing (e.g. while price is dropping or increasing), number of messages, contents of messages, message senders and measuring the response behaviours of the non-bot (actual traders).
For a business management research study about Job Market trends and changes in job characteristics, job description and required skill sets mass data collected from 2 different Job Advertisement Web Sites of the UK.
The collected data was used for some text analytics and natural language processing on job market analytics and finding trends and skill set groups in the job market.
For automated ranking of the publication performance of the academic position applicants in a university finance department, we have created a data collecting system from academic publication databases, top ranking academic journal databases, top ranking conference proceedings databases, top-100 finance departments web sites.
The data collected automatically used for ranking the publication performance of the applicants and used as a decision support systems during the selection process.
For a medical research study on piloting a new approach on education of medical faculty students by creating automated books from PubMED database by using some filterings such as course curriculum and MeSH Tree terms.
For a commercial project, a real time data collection system built for getting the list of seller, book lists and price list for used books on a website which is one of the biggest e-commerce platform of the Netherlands.
The collected is being collected in real time was used for automated pricing on the used books by checking all the other sellers and prices for the same books.
For a worldwide fashion retailer which trades more than 60 different countries:
Select 6 different countries among these 60 countries.
Select top 3 competitors in each country
Select 10 different categories for the products range
Automatically collect data for all of the countries, competitors, product detail (title, description, images, original price, discounted price) for all these segments described above.
The main motivation for this work for the company is to review their international pricing policy and see whether they are over-pricing or under-pricing for the given countries and categories.
For a commercial company working on clearance / security check for the guests in a short term accommodating platform, real time data collection / data search systems built for checking the details of the guests against the open source databases such as sanctions lists, most wanted lists, state public lists.
For more information and getting free quote for your data collection requirements
E-Mail us at: researchminer@infomerge.co.uk
ResearchMiner is an Infomerge Group Company focused on Academic Data Collection.