16 Matching Annotations
  1. Apr 2022
    1. How to earn good backlinks for free 2022 afterwardsThe proven ways to earn SEO backlinks at no cost at all - No spamming No harmful software No spend a dimeWhat is backlink? Know the backlink definition from the expert. Find out backlink meaning on Semrush BlogThe proven ways to earn SEO backlinks at no cost at all. No need money to pay SEO agency. No black hat tricks and fast result. More than 300 good domains available as your target link building. To be honest, they are SEO checker, website value estimator, Whois Api sites, Alexa ranks , scam checking tools and so on. They will check and record your site (cached) for different time ranges, sometime recorded permanently and that's your backlinks (short story btw). Most of those sites are partner of Turbo SEO Reviewer network and many thanks to the founder of Turbo SEO organization, we could do more SEO troubleshoots and feel much better with your free SEO tools ;)So, copy paste these domains on your browser, insert your own domain or website onto their test box, click the URLs that link back to your website (if available) to let crawler bot know about a new page that contains your backlink, wait around 3 - 7 days, check your SEO tools dashboard, for example Semrush new backlink monitor or even you can use  your GSC as well (although slower in appearance rather than Semrush).There are several ways to create backlinks for free:1. Check  your site's SEO score on their homepage2. Give good comments properly and then add your link onto form they provide. You may post good comment such as appreciate his articles but don't spam their sites3. Contact the author if the site is not SEO checker and there is no comment box
    1. Open Knowledge Maps, meanwhile, is built on top of the open-source Bielefeld Academic Search Engine, which boasts more than 270 million documents, including preprints, and is curated to remove spam.

      Open Knowledge Maps uses the open-source Bielefeld Academic Search Engine and in 2021 indicated that it covers 270 million documents including preprints. Open Knowledge Maps also curates its index to remove spam.


      How much spam is included in the journal article space? I've heard of incredibly low quality and poorly edited journals, so filtering those out may be fairly easy to do, but are there smaller levels of individual spam below that?

    1. Algospeak refers to code words or turns of phrase users have adopted in an effort to create a brand-safe lexicon that will avoid getting their posts removed or down-ranked by content moderation systems. For instance, in many online videos, it’s common to say “unalive” rather than “dead,” “SA” instead of “sexual assault,” or “spicy eggplant” instead of “vibrator.”

      Definition of "Algospeak"

      In order to get around algorithms that demote content in social media feeds, communities have coined new words or new meanings to existing words to communicate their sentiment.

      This is affecting TikTok in particular because its algorithm is more heavy-handed in what users see. This is also causing people who want to be seen to tailor their content—their speech—to meet the algorithms needs. It is like search engine optimization for speech.

      Article discovered via Cory Doctorow at The "algospeak" dialect

  2. Jan 2022
    1. Budak, C., Soroka, S., Singh, L., Bailey, M., Bode, L., Chawla, N., Davis-Kean, P., Choudhury, M. D., Veaux, R. D., Hahn, U., Jensen, B., Ladd, J., Mneimneh, Z., Pasek, J., Raghunathan, T., Ryan, R., Smith, N. A., Stohr, K., & Traugott, M. (2021). Modeling Considerations for Quantitative Social Science Research Using Social Media Data. PsyArXiv. https://doi.org/10.31234/osf.io/3e2ux

  3. Sep 2021
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  10. Jun 2016
    1. indexer (donc, classer).

      Ok, en fait il s'agit de la catégorisation par l'auteur VS celle effectuée par les moteurs.

  11. May 2015
    1. That is, the human annotators are likely to assign different relevance labels to a document, depending on the quality of the last document they had judged for the same query. In addi- tion to manually assigned labels, we further show that the implicit relevance labels inferred from click logs can also be affected by an- choring bias. Our experiments over the query logs of a commercial search engine suggested that searchers’ interaction with a document can be highly affected by the documents visited immediately be- forehand.