https://www.bibsonomy.org/user/jaeschke/myownBibSonomy RSS Feed for /user/jaeschke/myownhttps://zenodo.org/records/15736201jaeschke2025-06-25T11:05:18+02:00dataset myown n-gram text twitter <a itemprop="url" data-versiondate="2025-06-25T11:05:18+02:00" href="https://zenodo.org/records/15736201" rel="nofollow" class="description-link">https://zenodo.org/records/15736201</a>Adventures in programming PostScripthttps://ps.igada.de/jaeschke2025-02-06T14:00:19+01:00myown postscript programming <span itemprop="description">Adventures in programming PostScript</span>An endeavour to reverse-engineer the file format of D-Sat 1.https://dsat.igada.de/jaeschke2024-06-28T07:57:54+02:00d-sat dsat engineering file format image myown reverse satellite <span itemprop="description">An endeavour to reverse-engineer the file format of D-Sat 1.</span>https://www.goethe-gesellschaft.de/podcast/folge-11-woerter-zaehlen-oder-die-top-10-von-goethes-substantiven-verben-und-adjektiven-was-geben-die-datenbanken-her/jaeschke2024-02-09T17:25:39+01:00dh goethe myown nlp podcast <a itemprop="url" data-versiondate="2024-02-09T17:25:39+01:00" href="https://www.goethe-gesellschaft.de/podcast/folge-11-woerter-zaehlen-oder-die-top-10-von-goethes-substantiven-verben-und-adjektiven-was-geben-die-datenbanken-her/" rel="nofollow" class="description-link">https://www.goethe-gesellschaft.de/podcast/folge-11-woerter-zaehlen-oder-die-top-10-von-goethes-substantiven-verben-und-adjektiven-was-geben-die-datenbanken-her/</a>Formal Concept Analysis for Digital Humanities https://fca4dh.algebra20.de/jaeschke2022-09-22T16:28:04+02:00algebra analysis concept dh digital fca formal humanities myown <span itemprop="description">Formal Concept Analysis for Digital Humanities </span>The dataset has been created in an effort to establish a knowledge base on the ``German Academic Web'' (GAW). Since 2012, semi-annual focused crawls of the web pages of universities and research institutes in Germany have been performed using Heritrix, the open source archival quality web crawler of the Internet Archive. Starting from a list of given seeds, follows newly discovered hyperlinks and stores seen content in the standardised WARC file format. For each crawl, Heritrix was initialised with a conceptually invariant seed list of, on average, 150 domains of all German academic institutions with the right to award doctorates. The seed list is extracted from the current entries on https://de.wikipedia.org/wiki/Liste_der_Hochschulen_in_Deutschland The crawler follows a breadth-first policy on each host, thereby collecting all available pages reachable by links from the homepage. The scope was limited to crawl only pages from the seed domains and certain file types (mainly audio, video, and compressed files) were excluded using regular expressions.  Along the crawl, the URL queues were monitored via a web UI. Hosts that appeared to be undesirable, such as e-learning systems or repositories, were `retired', that is, their URLs no longer crawled. However, previously harvested URLs from retired hosts were not removed. Most crawls were finished (manually) after roughly 100 million pages were collected (according to Heritrix' control console), which took roughly two weeks per crawl, on average.  The present data set presents an overview of the size of the GAW.https://zenodo.org/record/3843507jaeschke2022-03-02T11:38:42+01:00dataset gaw myown regio zenodo <span itemprop="description">The dataset has been created in an effort to establish a knowledge base on the ``German Academic Web&#039;&#039; (GAW). Since 2012, semi-annual focused crawls of the web pages of universities and research institutes in Germany have been performed using Heritrix, the open source archival quality web crawler of the Internet Archive. Starting from a list of given seeds, follows newly discovered hyperlinks and stores seen content in the standardised WARC file format. For each crawl, Heritrix was initialised with a conceptually invariant seed list of, on average, 150 domains of all German academic institutions with the right to award doctorates. The seed list is extracted from the current entries on https://de.wikipedia.org/wiki/Liste_der_Hochschulen_in_Deutschland The crawler follows a breadth-first policy on each host, thereby collecting all available pages reachable by links from the homepage. The scope was limited to crawl only pages from the seed domains and certain file types (mainly audio, video, and compressed files) were excluded using regular expressions.  Along the crawl, the URL queues were monitored via a web UI. Hosts that appeared to be undesirable, such as e-learning systems or repositories, were `retired&#039;, that is, their URLs no longer crawled. However, previously harvested URLs from retired hosts were not removed. Most crawls were finished (manually) after roughly 100 million pages were collected (according to Heritrix&#039; control console), which took roughly two weeks per crawl, on average.  The present data set presents an overview of the size of the GAW.</span>This special issue seeks to invite scholars interested in using Wikipedia and related Linked Open Data projects as a new kind of source to study literary reception. https://culturalanalytics.org/post/958-cfp-world-literature-and-wikipediajaeschke2021-05-17T08:56:13+02:002021 cfp dh literature myown wikidata wikipedia world <span itemprop="description">This special issue seeks to invite scholars interested in using Wikipedia and related Linked Open Data projects as a new kind of source to study literary reception. </span>https://operas-ger.hypotheses.org/189jaeschke2021-03-04T12:26:17+01:002021 interview myown openaccess <a itemprop="url" data-versiondate="2021-03-04T12:26:17+01:00" href="https://operas-ger.hypotheses.org/189" rel="nofollow" class="description-link">https://operas-ger.hypotheses.org/189</a>https://slides.igada.de/2020-11-11-korpuslinguistik/jaeschke2020-11-11T19:24:11+01:002020 myown talk vossanto <a itemprop="url" data-versiondate="2020-11-11T19:24:11+01:00" href="https://slides.igada.de/2020-11-11-korpuslinguistik/" rel="nofollow" class="description-link">https://slides.igada.de/2020-11-11-korpuslinguistik/</a>https://data.gesis.org/tweetskb/jaeschke2020-06-09T16:26:46+02:00data dataset lod media myown rdf social tweets tweetskb twitter <a itemprop="url" data-versiondate="2020-06-09T16:26:46+02:00" href="https://data.gesis.org/tweetskb/" rel="nofollow" class="description-link">https://data.gesis.org/tweetskb/</a>Vossian antonomasia is a stylistic device which attributes a certain property to a person by naming another (more well-known, more popular) person as a reference point. For instance, when Jim Koch is described as “the Steve Jobs of Beer”, certain qualities of Steve Jobs, be it entrepreneurship or persuasiveness, are assigned to Jim Koch, co-founder and chairman of the Boston Beer Company. VAs consist of three parts: a source (in our example “Steve Jobs”) serves as paragon to elevate the target (“Jim Koch”) by applying a modifier (“of Beer”) that provides the corresponding context. VA is named after Gerardus Vossius (1577– 1649), the Dutch classical scholar and author of rhetorical textbooks, who first distinguished and described VA as a separate phenomenon.https://vossanto.weltliteratur.net/jaeschke2019-12-19T11:56:06+01:00antonomasia antonomasie corpus dh digital humanities linguistics linguistik myown nyt va vossanto vossian vossianische vossius wikidata <span itemprop="description">Vossian antonomasia is a stylistic device which attributes a certain property to a person by naming another (more well-known, more popular) person as a reference point. For instance, when Jim Koch is described as “the Steve Jobs of Beer”, certain qualities of Steve Jobs, be it entrepreneurship or persuasiveness, are assigned to Jim Koch, co-founder and chairman of the Boston Beer Company. VAs consist of three parts: a source (in our example “Steve Jobs”) serves as paragon to elevate the target (“Jim Koch”) by applying a modifier (“of Beer”) that provides the corresponding context. VA is named after Gerardus Vossius (1577– 1649), the Dutch classical scholar and author of rhetorical textbooks, who first distinguished and described VA as a separate phenomenon.</span>https://lehkost.github.io/slides/2019-06-14-potsdam-fontane/jaeschke2019-06-17T10:15:24+02:002019 dh fontane myown vortrag <a itemprop="url" data-versiondate="2019-06-17T10:15:24+02:00" href="https://lehkost.github.io/slides/2019-06-14-potsdam-fontane/" rel="nofollow" class="description-link">https://lehkost.github.io/slides/2019-06-14-potsdam-fontane/</a>http://slides.igada.de/2017-10-10-ischool/#/jaeschke2018-06-08T13:54:58+02:00dh myown nyt vossanto <a itemprop="url" data-versiondate="2018-06-08T13:54:58+02:00" href="http://slides.igada.de/2017-10-10-ischool/#/" rel="nofollow" class="description-link">http://slides.igada.de/2017-10-10-ischool/#/</a>https://lehkost.github.io/slides/2017-bern/#/jaeschke2018-06-08T13:54:43+02:00dh dhd folien myown slides vortrag vossanto <a itemprop="url" data-versiondate="2018-06-08T13:54:43+02:00" href="https://lehkost.github.io/slides/2017-bern/#/" rel="nofollow" class="description-link">https://lehkost.github.io/slides/2017-bern/#/</a>https://github.com/weltliteratur/vossantojaeschke2018-06-08T09:03:33+02:00github myown vossanto <a itemprop="url" data-versiondate="2018-06-08T09:03:33+02:00" href="https://github.com/weltliteratur/vossanto" rel="nofollow" class="description-link">https://github.com/weltliteratur/vossanto</a>For what reasons do academics follow one another on Twitter? Robert Jäschke, Stephanie B. Linek and Christian P. Hoffmann analysed the Twitter activity of computer scientists and found that while the quality of information provided by a Twitter account is a key motive for following academic colleagues, there is also evidence of a career planning motive. As well as there being reciprocal following between users of the same academic status (except, remarkably, between PhD researchers), a form of strategic politeness can be observed whereby users follow those of higher academic status without necessarily being followed back. The emerging academic public sphere facilitated by Twitter is largely shaped by dynamics and hierarchies all too familiar to researchers struggling to plot their careers in academia.http://blogs.lse.ac.uk/impactofsocialsciences/2017/10/03/new-media-familiar-dynamics-academic-hierarchies-influence-academics-following-behaviour-on-twitter/jaeschke2017-10-03T14:22:23+02:002017 myown open reciprocity research science science2.0 twitter <span itemprop="description">For what reasons do academics follow one another on Twitter? Robert Jäschke, Stephanie B. Linek and Christian P. Hoffmann analysed the Twitter activity of computer scientists and found that while the quality of information provided by a Twitter account is a key motive for following academic colleagues, there is also evidence of a career planning motive. As well as there being reciprocal following between users of the same academic status (except, remarkably, between PhD researchers), a form of strategic politeness can be observed whereby users follow those of higher academic status without necessarily being followed back. The emerging academic public sphere facilitated by Twitter is largely shaped by dynamics and hierarchies all too familiar to researchers struggling to plot their careers in academia.</span>The files in this dataset are used to analyse the tweeting behaviour of computer scientists on Twitter. They comprise a set of 989,529 tweet-URL pairs (tweets_2014_researcher.tsv.bz2) from 2014 from 6,271 users of the computer scientists sample in https://zenodo.org/record/12942 specified by time, tweet id, user id, and URL, a set of 300,053,850 tweet ids (tweets_2014_sample.tsv.bz2) from the 1% Twitter stream sample from 2014, a set of 605,080 tweet-URL pairs (tweets_2014_sample_6694_users.tsv.bz2) from the 1% Twitter stream sample from 2014 for 6,694 users specified by time, tweet id, user id, and URL, a set of the top 10,000 host names (MAG_hosts_10000.tsv) from the Microsoft Academic Graph data (http://blogs.msdn.com/b/msr_er/archive/2015/06/26/announcing-the-microsoft-academic-graph-let-the-research-begin.aspx), specified by rank, URL count, and host name, and a set of 340 host names of URL shortening services (url_shortening_services.tsv). In addition, the following rankings (based on the odds ratio) of domains, hosts, and URLs that appear in both the researcher dataset and the sample are included: domains_by_odds_ratio.tsv.bz2 - a ranking of 61,860 domains, hosts_by_odds_ratio.tsv.bz2 - a ranking of 80,384 hosts, publisher_domains_by_odds_ratio.tsv.bz2 - a ranking of 924 publisher domains, publisher_urls_by_odds_ratio.tsv.bz2 - a ranking of 4,227 publisher URLs.https://zenodo.org/record/580587jaeschke2017-06-26T11:46:10+02:002017 dataset myown twitter <span itemprop="description">The files in this dataset are used to analyse the tweeting behaviour of computer scientists on Twitter. They comprise a set of 989,529 tweet-URL pairs (tweets_2014_researcher.tsv.bz2) from 2014 from 6,271 users of the computer scientists sample in https://zenodo.org/record/12942 specified by time, tweet id, user id, and URL, a set of 300,053,850 tweet ids (tweets_2014_sample.tsv.bz2) from the 1% Twitter stream sample from 2014, a set of 605,080 tweet-URL pairs (tweets_2014_sample_6694_users.tsv.bz2) from the 1% Twitter stream sample from 2014 for 6,694 users specified by time, tweet id, user id, and URL, a set of the top 10,000 host names (MAG_hosts_10000.tsv) from the Microsoft Academic Graph data (http://blogs.msdn.com/b/msr_er/archive/2015/06/26/announcing-the-microsoft-academic-graph-let-the-research-begin.aspx), specified by rank, URL count, and host name, and a set of 340 host names of URL shortening services (url_shortening_services.tsv). In addition, the following rankings (based on the odds ratio) of domains, hosts, and URLs that appear in both the researcher dataset and the sample are included: domains_by_odds_ratio.tsv.bz2 - a ranking of 61,860 domains, hosts_by_odds_ratio.tsv.bz2 - a ranking of 80,384 hosts, publisher_domains_by_odds_ratio.tsv.bz2 - a ranking of 924 publisher domains, publisher_urls_by_odds_ratio.tsv.bz2 - a ranking of 4,227 publisher URLs.</span>http://www.altmetrics.ntuchess.com/AROSIM2018/jaeschke2017-06-20T10:01:49+02:002018 altmetrics myown workshop <a itemprop="url" data-versiondate="2017-06-20T10:01:49+02:00" href="http://www.altmetrics.ntuchess.com/AROSIM2018/" rel="nofollow" class="description-link">http://www.altmetrics.ntuchess.com/AROSIM2018/</a>http://www.sobigdata.eu/dataset/german-academic-webjaeschke2017-04-04T13:17:43+02:00academic dataset gaw german myown sobigdata web <a itemprop="url" data-versiondate="2017-04-04T13:17:43+02:00" href="http://www.sobigdata.eu/dataset/german-academic-web" rel="nofollow" class="description-link">http://www.sobigdata.eu/dataset/german-academic-web</a>https://www.sheffield.ac.uk/is/staff/jaeschkejaeschke2016-07-28T17:01:33+02:00myown sheffield <a itemprop="url" data-versiondate="2016-07-28T17:01:33+02:00" href="https://www.sheffield.ac.uk/is/staff/jaeschke" rel="nofollow" class="description-link">https://www.sheffield.ac.uk/is/staff/jaeschke</a>