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MIDA Local Training 2th Nov. 2020 → 7th Nov. 2020 Philipps - Marburg University Monday 2nd November : In order to scrape data from websites or to parse already existing data (Wikipedia) researchers need to learn the fundamentals of HTML, XML, and BeautifulSoup Tuesday 3rd November : Certain platforms such as Twitter disclose their data via an API. Researchers willing to receive this data need to learn how to communicate with APIs Wednesday 4th November : After data has been gathered it has to be exported and/or parsed in ways that allow it to be visualized or parsed by machine learning packages. Thursday 5th November : Students will also get the chance to revisit concepts from prior days and continue to exercise with these concepts in case they do not have project specific issues. Friday 6th November : Students will also get the chance to revisit concepts from prior days and continue to exercise with these concepts in case they do not have project specific issues. Saturday 7th November : Students will also get the chance to revisit concepts from prior days and continue to exercise with these concepts in case they do not have project specific issues. [...]
GRAPHIC DESIGN, LOCAL TRAINING, SOCIAL SCIENCES, Philipps - Marburg University, ITN MIDA, ISLAM, PROGRAMME
GRAPHIC DESIGN, LOCAL TRAINING, SOCIAL SCIENCES, Philipps - Marburg University, ITN MIDA, ISLAM, PROGRAMME
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 4 | |
| downloads | 2 |

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