Long trends on twitter: intertemporal clusters combining hashtags and terms on Scientometrics, Altmetrics, Bibliometrics and Science Of Science

Long trends on twitter: inter-temporal clusters combining hashtags and terms, for all tweets on Scientometrics, Altmetrics, Bibliometrics and Science Of Science from Jan. 2017 to dec. 2021, on a semester base.

Query used to extract tweets: lang:en (Scientometrics OR “ScienceOfScience” OR “Science Of Science” OR “Altmetrics” OR “altmetric” OR “bibliometrics” OR “bibliometric” OR “citation metrics” OR “citation analysis” OR “co-citation analysis” OR “cocitation analysis” OR “bibliographic coupling” OR “co-word analysis” OR “co-authorship analysis”) -is:retweet

It gathers 80078 tweets for the period, which were downloaded using Twitter API for Academic Research and preprocessed with Excel. A lexical extraction was performed by combining keywords and hashtags. Finally, a co-occurrence analysis was performed on the extracted keywords and hashtags, and mapped over time across 10 overlapping time periods (semesters). Cluster and stream names are the two central keywords of clusters.

Do you find what you are expecting?

With some pending questions:
1/ why #ornithology are there since the beginning, and so active
2/ #phdchat #phdlife move from one cluster discussing about gender balance and research systems in 2017, to another focused on research metrics and #altmetrics from mid 2019 to mid 2021
3/ #rstats #bibliometrix and #biblioshiny are in a stable stream, since 2018-2019. Discussing #citationanalysis and some other #scientometrics methods

4/ in 2019, unsurprisingly, has emerged #covid and #covid19 in a narrow cluster: focused on opening and sharing researches. To gradually, in 2020 and 2021, discuss broader issues (#covidvaccine #preprints #psychology #publichealth)

See the full visualization on Label editor Tool from CorTexT Manager.