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Search for articles/news/research paper based on user defined keywords . Export the list of news items to a [login to […]

Search for articles/news/research paper based on user defined keywords . Export the list of news items to a [login to view URL] equivalent. Attach news items’ hyperlink, chart, tables. Brief summary of the news.

I would like to scrap news on the internet and in my email inbox. The output news items should be dynamic based on keywords I choose and value I give. I made up an example using dictionary function below. since there are millions of articles on the internet and in my inbox, I would like to filter on only recent ones (e.g. recent 2 weeks) and articles are most likely interest me (e.g. a list of key words), by summing up the value of the keywords. I would like the [login to view URL] to have a list of the top 20 articles ranked by the total value calculated earlier. Then append the hyperlink, any table, graph to each of the news item and briefly summary of the article. The final [login to view URL] should looks like a newsletter with a list that contains news subject, hyperlink, table, graph and a brief summary.

Subject: xxx

Summary: xxx

Date: xxx

Link: http:xxx

Table, Chart, Graph etc

Newsletter ideas of approach

search news in (they may need to be two separate .py):

a. email inbox news (gmail and outlook).py

b. web news (google or a list of news websites).py – see appendix (list of news websites)

To do:

1) Search for articles/news/research paper in the last two weeks based on user defined keywords and assigned values. Please use any method as you see fit

e.g.

dict = {climate:3, green:2, house:1). if an article has all 3 words, it scores 6. but if an article has all 3 words twice, it still scores 6

Notes: in the keywords search please ignore

▪ capital letters (Climate = climate)

▪ repetitions (each keywords is summed only once)

▪ abbreviations (UK = United Kingdom)

3) Rank the news items in the last 2 weeks by sum of keywords’ value.

e.g. dict = {climate:3, green:2, house:1)

A article mentioned both climate and green then it has a value of 5

B article mentioned both climate, green and house then it has a value of 6

C article mentioned both climate and house then it has a value of 4

The rank of the article is B, A, C

4) Export the list of news items to a [login to view URL] equivalent.

5) Attach news items’ source hyperlink, graph, chart to each of the news item.

e.g. if the article scored into top 20 append source link and graph/table in the article content.

6) Brief summary of the news. I think it needs NLTK package.

Appendix (list of keywords):

Brexit = 5

ABS = 5

RMBS = 5

CMBS = 5

Student Loans = 5

NPL = 5

NPE = 5

Mortgages = 5

Structured Finance = 4

FED = 4

ECB = 4

Climate Change = 4

Green Bond = 4

ESG = 4

Appendix (list of news websites):

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Skills: Python, Natural Language, Web Scraping, BeautifulSoup, Scrapy

See more:
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London, United Kingdom

Project ID: #26732886

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