What is newsworthy about Covid-19? A corpus linguistic analysis of news values in reports by China Daily and The New York Times Humanities and Social Sciences Communications

Counting the unique words in our data gives an idea about our data’s most frequent, least frequent terms. Often we drop the least frequent comments to make our model training more generalized. I am converting the raw text data into a pandas data frame and performing various data cleaning techniques. We should note that facet processing must be run against a static set of content, and the results are not applicable to any other set of content. In other words, facets only work when processing collections of documents.

IBM has innovated in the AI space by pioneering NLP-driven tools and services that enable organizations to automate their complex business processes while gaining essential business insights. Is as a method for uncovering hidden structures in sets of texts or documents. In essence it clusters texts to discover latent topics based on their contents, processing individual words and assigning them values based on their distribution. This technique is based on the assumptions that each document consists of a mixture of topics and that each topic consists of a set of words, which means that if we can spot these hidden topics we can unlock the meaning of our texts. Stop words can be safely ignored by carrying out a lookup in a pre-defined list of keywords, freeing up database space and improving processing time. Splitting on blank spaces may break up what should be considered as one token, as in the case of certain names (e.g. San Francisco or New York) or borrowed foreign phrases (e.g. laissez faire).

Cognition and NLP

Sentiment analysis is the automated process of classifying opinions in a text as positive, negative, or neutral. You can track and analyze sentiment in comments about your overall brand, a product, particular feature, or compare your brand to your competition. NLP is an exciting and rewarding discipline, and has potential to profoundly impact the world in many positive ways. Unfortunately, NLP is also the focus of several controversies, and understanding them is also part of being a responsible practitioner. For instance, researchers have found that models will parrot biased language found in their training data, whether they’re counterfactual, racist, or hateful. Moreover, sophisticated language models can be used to generate disinformation.

NLP is growing increasingly sophisticated, yet much work remains to be done. Current systems are prone to bias and incoherence, and occasionally behave erratically. Despite the challenges, engineers have many opportunities to apply NLP in ways that are ever more central to a functioning society.

What is natural language processing?

Semantic tasks analyze the structure of sentences, word interactions, and related concepts, in an attempt to discover the meaning of words, as well as understand the topic of a text. Basically, they allow developers and businesses to create a software that understands human language. Due to the complicated nature of human language, NLP can be difficult to learn and implement correctly. However, with the knowledge gained from this article, you will be better equipped to use NLP successfully, no matter your use case.

Read more about https://www.metadialog.com/ here.