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zenodo44/100

MIGR-TWIT Corpus. Migration Tweets of right and far-right politics in Europe

<p><strong>Description</strong></p> <p>The <strong>MIGR-TWIT Corpus</strong> is a multilingual corpus of tweets about the topic of migration in Europe. Within the framework of the collaborative research project OLiNDiNUM (Observatoire LINguistique du DIscours NUM&eacute;rique, Linguistic Observatory of Online Debate) the MIGR-TWIT Corpus is created with the aim of developing language databases of online debate. Considering the global issue of migration in line with British and French political contexts of last dozen years from 2011 to 2022, the corpus consists of two sub-corpora:&nbsp;</p> <ul> <li> <p><strong>FR-R-MIGR-TWIT-2011-2022 Corpus </strong>for French language data (1 January 2011 - 30 June 2022) and&nbsp;</p> </li> <li> <p><strong>UK-R-MIGR-RA-TWIT-2012-2022 Corpus </strong>for English language data (1 January 2012 - 5 September 2022)&nbsp;<strong>&nbsp;</strong></p> </li> </ul> <p>Using the Twitter API v2 Academic Research, tweets containing at least one occurrence of migration or refugee related words are retrieved automatically from 28 right and far-right political figures and parties. The whole corpus contains 18,233&nbsp; tweets and 533,198 words.&nbsp;</p> <p><strong>Scientific reference:</strong></p> <p>Pietrandrea, P., Battaglia, E. (2022). &ldquo;Migrants and the EU&rdquo;. The diachronic construction of ad hoc categories in French far-right discourse. Journal of Pragmatics 192, 139-157.</p> <p>Blandino, G. (2023). <em>10 years of public debate on immigration: combining topic modeling and corpus linguistics to examine the British (far-)right discourse on Twitter</em>, MA University of Wolverhampton</p> <p>Jeon, S. (2025). Le discours num&eacute;rique sur l'immigration en France entre 2011 et 2022. Une analyse de corpus (Online Discourse on Immigration in France between 2011 and 2022. A Corpus Analysis), PhD Thesis, Universit&eacute; de Lille, France.</p> <p><strong>Contents</strong></p> <p>The whole corpus contains two CSV Zip files (tabular format) corresponding to each sub-corpus. The complete corpus is presented in two versions, one version with the tweet identifier (<strong><em>data__id</em></strong>) and the text of the tweet (<strong><em>data__text</em></strong>) as a header (folders named <em>FR-R-MIGR-TWIT-2011-2022_textonly</em> and <em>UK-R-MIGR-RA-TWIT-2012-2022_textonly</em>, respectively composed of 12 and 11 Zip files of every single year), and the other version with all tweet fields information included as a header, such as the posting date (<em><strong>data__created__at</strong></em>), the username (<strong><em>author__name</em></strong>), the number of retweets (<em><strong>data__public_metrics__retweet_count</strong></em>), etc.,&nbsp;with two folders named <em>FR-R-MIGR-TWIT-2011-2022_meta</em> and <em>UK-R-MIGR-RA-TWIT-2012-2022_meta</em>. Detailed information for each sub-corpus is illustrated below.</p> <p><strong>1. FR-R-MIGR-TWIT-2011-2022&nbsp;&nbsp;</strong></p> <ul> <li><strong>Created at: </strong>2022-08-08</li> <li> <p><strong>Language: </strong>FR<strong>&nbsp;</strong></p> </li> <li> <p><strong>Coverage: </strong>16 user accounts; 11,761 tweets; 358,491 words</p> </li> <li> <p><strong>Time of data collection: </strong>start=2011-01-01; end=2022-06-30&nbsp;</p> </li> <li> <p><strong>Keywords: </strong>words derived from a latin root &ldquo;<em><strong>migr</strong></em>&rdquo; of <em>migrare</em></p> </li> <li> <p><strong>Corpus composition:&nbsp;</strong></p> </li> </ul> <table> <tbody> <tr> <th>&nbsp;</th> <th>Political figure/party</th> <th>Username</th> <th>Tweets</th> <th>Year concerned</th> </tr> <tr> <th>1</th> <td>Michel Barnier</td> <td>@MichelBarnier</td> <td>31</td> <td>2017-22</td> </tr> <tr> <th>2</th> <td>Val&eacute;rie P&eacute;cresse</td> <td>@vpecresse</td> <td>81</td> <td>2017-22</td> </tr> <tr> <th>3</th> <td>Rassemblement National</td> <td>@RNational_off</td> <td>3,347</td> <td>2017-22</td> </tr> <tr> <th>4</th> <td>Nicolas Dupont-aignan</td> <td>@dupontaignan</td> <td>663</td> <td>2011-22</td> </tr> <tr> <th>5</th> <td>&Eacute;ric Ciotti</td> <td>@ECiotti</td> <td>1,007</td> <td>2012-22</td> </tr> <tr> <th>6</th> <td>Christian Estrosi</td> <td>@cestrosi</td> <td>137</td> <td>2011-22</td> </tr> <tr> <th>7</th> <td>Marine Le Pen</td> <td>@MLP_officiel</td> <td>1,650</td> <td>2011-22</td> </tr> <tr> <th>8</th> <td>Val&eacute;rie Boyer</td> <td>@valerieboyer13</td> <td>837</td> <td>2012-22</td> </tr> <tr> <th>9</th> <td>Florian Philippot</td> <td>@f_philippot</td> <td>485</td> <td>2012-22</td> </tr> <tr> <th>10</th> <td>Xavier Bertrand</td> <td>@xavierbertrand</td> <td>70</td> <td>2017-22</td> </tr> <tr> <th>11</th> <td>Marion Mar&eacute;chal</td> <td>@MarionMarechal</td> <td>479</td> <td>2012-17,19-22</td> </tr> <tr> <th>12</th> <td>Philippe Meunier</td> <td>@Meunier_Ph</td> <td>245</td> <td>2013-22</td> </tr> <tr> <th>13</th> <td>Jordan Bardella</td> <td>@J_Bardella</td> <td>1,095</td> <td>2013-22</td> </tr> <tr> <th>14</th> <td>Nicolas Bay</td> <td>@NicolasBay_</td> <td>1,260</td> <td>2017-22</td> </tr> <tr> <th>15</th> <td>Emmanuel Macron</td> <td>@EmmanuelMacron</td> <td>72</td> <td>2017-22</td> </tr> <tr> <th>16</th> <td>&Eacute;ric Zemmour</td> <td>@ZemmourEric</td> <td>302</td> <td>2019-22</td> </tr> <tr> <th>17</th> <td>Jean Messiha*</td> <td>Banned from Twitter (since July 2021)</td> <td>-</td> <td>-</td> </tr> </tbody> </table> <ul> <li>Political figures and parties of table above are listed in chronological order according to the dates on which they posted their first tweet.</li> <li> <p><strong>*</strong>Before the launching of Twitter API v2 Academic Research, migr-tweets were collected from the database of Europresse.com including 1,453 tweets of Jean Messiha as part of the reference study (Pietrandrea &amp; Battaglia 2022). However, the Twitter account in question has been permanently banned since July 2021. For our data collection using the Twitter API started in September 2021, we could not&nbsp;access this account. Therefore, we decided not to include his tweets in the FR-R-MIGR-TWIT-2011-2022 for the sake of consistency with the rest of twitter data that are automatically retrieved.</p> </li> <li> <p>The sub-corpus FR-R-MIGR-TWIT-2017-2022 is developed, annotated and analyzed as part of a doctoral thesis in progress (<a href="https://theses.fr/s360032">Jeon, 2025</a>) with the aim of studying the semantic construction of migr-lexicon over the period between 2011 and 2022.&nbsp;</p> </li> </ul> <p><strong>&nbsp;</strong></p> <p><strong>2. UK-R-MIGR-RA-TWIT-2012-2022&nbsp;</strong></p> <ul> <li> <p><strong>Created at: </strong>2022-09-06</p> </li> <li> <p><strong>Language: </strong>EN</p> </li> <li> <p><strong>Coverage: </strong>12 user accounts; 6,472 tweets; 174,707 words&nbsp;</p> </li> <li> <p><strong>Time of data collection: </strong>start=2012-01-01; end=2022-09-05</p> </li> <li> <p><strong>Keywords: </strong>words derived from a latin root &ldquo;<strong><em>migr</em></strong>&rdquo; of <em>migrare </em>in addition to the keywords &ldquo;<strong><em>refugee</em></strong>(<strong><em>s</em></strong>)&rdquo; and &ldquo;<strong><em>asylum</em></strong>&rdquo;.</p> </li> <li> <p><strong>Corpus composition:</strong></p> </li> </ul> <table> <tbody> <tr> <th>&nbsp;</th> <th>Political figure/party</th> <th>Username</th> <th>Tweets</th> <th>Year concerned</th> </tr> </tbody> <tbody> <tr> <th>1</th> <td>David Cameron</td> <td>@David_Cameron</td> <td>32</td> <td>2012-22</td> </tr> <tr> <th>2</th> <td>Amber Rudd</td> <td>@AmberRuddUK</td> <td>29</td> <td>2012-22</td> </tr> <tr> <th>3</th> <td>Sajid Javid</td> <td>@sajidjavid</td> <td>84</td> <td>2012-22</td> </tr> <tr> <th>4</th> <td>Boris johnson</td> <td>@BorisJohnson</td> <td>80</td> <td>2015-22</td> </tr> <tr> <th>5</th> <td>Priti Patel</td> <td>@pritipatel</td> <td>304</td> <td>2012-22</td> </tr> <tr> <th>6</th> <td>UK Home Office</td> <td>@ukhomeoffice</td> <td>909</td> <td>2012-22</td> </tr> <tr> <th>7</th> <td>Nigel Farage</td> <td>@Nigel_Farage</td> <td>1,010</td> <td>2012-22</td> </tr> <tr> <th>8</th> <td>Richard Tice</td> <td>@TiceRichard</td> <td>180</td> <td>2013-22</td> </tr> <tr> <th>9</th> <td>UKIP</td> <td>@UKIP</td> <td>2,746</td> <td>2012-22</td> </tr> <tr> <th>10</th> <td>Neil Hamilton</td> <td>@NeilUKIP</td> <td>252</td> <td>2013-22</td> </tr> <tr> <th>11</th> <td>Nick Griffin</td> <td>@NickGriffinBU</td> <td>542</td> <td>2012-22</td> </tr> <tr> <th>12</th> <td>Robin Tilbrook</td> <td>@RobinTilbrook</td> <td>304</td> <td>2012-22</td> </tr> </tbody> </table> <p>&nbsp;</p> <ul> <li> <p>2 out of 12 accounts are official accounts belonging to the&rdquo; UK Home Office&rdquo; department and the &ldquo;UKIP&rdquo; (United Kingdom Independence Party) party. 10 out of 12 accounts are political figures&rsquo; accounts.</p> </li> <li> <p>The corpus UK-R-MIGR-RA-TWIT-2012-2022 will be exploited for the following master&rsquo;s thesis: Blandino, G. (2023). <em>10 years of public debate on immigration: combining topic modeling and corpus linguistics to examine the British (far-)right discourse on Twitter</em>, MA University of Wolverhampton.</p> </li> </ul> <p>&nbsp;</p>

opencc-by-4.0Nov 2022View details →
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Рис. 3. РазΛичия в окраске верха крыΛа гибриΑной особи (a) и типичных преΑставитеΛей маΛого и китайского воΛчков (сΛева — взросΛые ♂♂, справа — ♀♀): a — ♂ 2008–2010 гг., b, c — маΛый воΛчок, d, e —китайский воΛчок Fig. 3. Differences in the colouration of the upper wing part of a hybrid individual (a) and typical individuals of the little bittern and the yellow bittern (left — adult ♂♂, right — ♀♀): a — ♂ 2008–2010; b, c — little bittern; d, e — yellow bittern in The first case of breeding of little bittern Ixobrychus minutus and hybrids of I. minutus with I. sinensis in the Russian Far East

Рис. 3. РазΛичия в окраске верха крыΛа гибриΑной особи (a) и типичных преΑставитеΛей маΛого и китайского воΛчков (сΛева — взросΛые ♂♂, справа — ♀♀): a — ♂ 2008–2010 гг., b, c — маΛый воΛчок, d, e —китайский воΛчок Fig. 3. Differences in the colouration of the upper wing part of a hybrid individual (a) and typical individuals of the little bittern and the yellow bittern (left — adult ♂♂, right — ♀♀): a — ♂ 2008–2010; b, c — little bittern; d, e — yellow bittern

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Рис. 4. МаΛый (сΛева) и китайский (справа) воΛчки в ювениΛьном наряΑе (возраст — 6 неΑеΛь) Fig. 4. Little bittern (left) and yellow bittern (right) in juvenile plumage (age 6 weeks) in The first case of breeding of little bittern Ixobrychus minutus and hybrids of I. minutus with I. sinensis in the Russian Far East

Рис. 4. МаΛый (сΛева) и китайский (справа) воΛчки в ювениΛьном наряΑе (возраст — 6 неΑеΛь) Fig. 4. Little bittern (left) and yellow bittern (right) in juvenile plumage (age 6 weeks)

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Рис. 5. Особенности окраски верха гоΛовы (a), спинных перьев (b) и верха крыΛа (c) у моΛоΑых птиц маΛого (a — сверху, b — сΛева, c — справа) и китайского (a — снизу, b — справа, c — сΛева) воΛчков Fig. 5. Colouration of the upper head (a), dorsal feathers (b), and upper covers (c) in young birds of little (a — above; b — left; c — right) and yellow (a — below; b — right; c — left) bitterns in The first case of breeding of little bittern Ixobrychus minutus and hybrids of I. minutus with I. sinensis in the Russian Far East

Рис. 5. Особенности окраски верха гоΛовы (a), спинных перьев (b) и верха крыΛа (c) у моΛоΑых птиц маΛого (a — сверху, b — сΛева, c — справа) и китайского (a — снизу, b — справа, c — сΛева) воΛчков Fig. 5. Colouration of the upper head (a), dorsal feathers (b), and upper covers (c) in young birds of little (a — above; b — left; c — right) and yellow (a — below; b — right; c — left) bitterns

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Рис. 1–10. Δичинка Onthophagus japonicus Harold, 1875. 1 – гоΛовная капсуΛа; 2 – эпифаринкс; 3 – Λевая манΑибуΛа, виΑ сверху; 4 – правая манΑибуΛа, виΑ сверху; 5 – Λевая манΑибуΛа, виΑ снизу; 6 – правая манΑибуΛа, виΑ снизу; 7 – Λевая максиΛΛа, виΑ сверху; 8 – Λевая максиΛΛа, виΑ снизу; 9 – анаΛьный стернит; 10 – анаΛьная пΛощаΑка. Figs 1–10. Larva of Onthophagus japonicus Harold, 1875. 1 – head capsule; 2 – epipharynx; 3 – left mandible, dorsal view; 4 – right mandible, dorsal view; 5 – left mandible, ventral view; 6 – right mandible, ventral view; 7 – left maxilla, dorsal view; 8 – left maxilla, ventral view; 9 – anal sternit (venter of 10th abdominal segment); 10 – anal plate (caudal view of 10th abdominal segment). in Description of the larva of Onthophagus japonicus Harold, 1875 (Coleoptera: Scarabaeidae) from the Russian Far East with a key to the known larvae of the genus

Рис. 1–10. Δичинка Onthophagus japonicus Harold, 1875. 1 – гоΛовная капсуΛа; 2 – эпифаринкс; 3 – Λевая манΑибуΛа, виΑ сверху; 4 – правая манΑибуΛа, виΑ сверху; 5 – Λевая манΑибуΛа, виΑ снизу; 6 – правая манΑибуΛа, виΑ снизу; 7 – Λевая максиΛΛа, виΑ сверху; 8 – Λевая максиΛΛа, виΑ снизу; 9 – анаΛьный стернит; 10 – анаΛьная пΛощаΑка. Figs 1–10. Larva of Onthophagus japonicus Harold, 1875. 1 – head capsule; 2 – epipharynx; 3 – left mandible, dorsal view; 4 – right mandible, dorsal view; 5 – left mandible, ventral view; 6 – right mandible, ventral view; 7 – left maxilla, dorsal view; 8 – left maxilla, ventral view; 9 – anal sternit (venter of 10th abdominal segment); 10 – anal plate (caudal view of 10th abdominal segment).

opencc-by-4.0Dec 2018View details →
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Data for manuscript "The Prevalence of Terms Denoting Far-right and Far-left Political Extremism in U.S. and U.K. News Media"

<p>This data set belongs to an academic manuscript examining longitudinally (2000-2019) the prevalence of terms denoting far-right and far-left political extremism in a large corpus of more than 32 million written news and opinion articles from 54 news media outlets popular in the United States and the United Kingdom.</p> <p>The textual content of news and opinion articles from the 54 outlets listed in the main manuscript is available in the outlet&#39;s online domains and/or public cache repositories such as Google cache (https://webcache.googleusercontent.com), The Internet Wayback Machine (https://archive.org/web/web.php), and Common Crawl (https://commoncrawl.org). We used derived word frequency counts from these sources. Textual content included in our analysis is circumscribed to articles headlines and main body of text of the articles and does not include other article elements such as figure captions.</p> <p>Targeted textual content was located in HTML raw data using outlet specific xpath expressions.&nbsp;Tokens were lowercased prior to estimating frequency counts.&nbsp;To prevent outlets with sparse text content for a year from distorting aggregate frequency counts, we only include outlet frequency counts from years for which there is at least 1 million words of article content from an outlet. This threshold was chosen to maximize inclusion in our analysis of outlets with sparse amounts of articles text per year.&nbsp;</p> <p>Yearly frequency usage of a target word in an outlet in any given year was estimated by dividing the total number of occurrences of the target word in all articles of a given year by the number of all words in all articles of that year. This method of estimating frequency accounts for variable volume of total article output over time.</p> <p>The list of compressed files in this data set is listed next:</p> <p>-analysisScripts.rar contains the analysis scripts used in the main manuscript&nbsp;</p> <p>-articlesContainingTargetWords.rar contains counts of target words in outlets articles as well as total counts of words in articles</p> <p>&nbsp;</p> <p>Usage Notes</p> <p>In a small percentage of articles, outlet specific XPath expressions failed to properly capture the content of the article due to the heterogeneity of HTML elements and CSS styling combinations with which articles text content is arranged in outlets online domains. As a result, the total and target word counts metrics for a small subset of articles are not precise. In a random sample of articles and outlets, manual estimation of target words counts overlapped with the automatically derived counts for over 90% of the articles.</p> <p>Most of the incorrect frequency counts were minor deviations from the actual counts such as for instance counting the word &quot;Facebook&quot; in an article footnote encouraging article readers to follow the journalist&rsquo;s Facebook profile and that the XPath expression mistakenly included as the content of the article main text. Some additional outlet-specific inaccuracies that we could identify occurred in &quot;The Hill&quot; and &quot;Newsmax&quot; news outlets where XPath expressions had some shortfalls at precisely capturing articles&rsquo; content. For &quot;The Hill&quot;, in years 2007-2009, XPath expressions failed to capture the complete text of the article in about 40% of the articles. This does not necessarily result in incorrect frequency counts for that outlet but in a sample of articles&rsquo; words that is about 40% smaller than the total population of articles words for those three years. In the case of &quot;NewsMax&quot;, the issue was that for some articles, XPath expressions captured the entire text of the article twice. Notice that this does not result in incorrect frequency counts. If a word appears x times in an article with a total of y words, the same frequency count will still be derived when our scripts count the word 2x times in the version of the article with a total of 2y words.</p> <p>To conclude, in a data analysis of 32 million articles, we cannot manually check the correctness of frequency counts for every single article and hundred percent accuracy at capturing articles&rsquo; content is elusive due to the small number of difficult to detect boundary cases such as incorrect HTML markup syntax in online domains. Overall however, we are confident that our frequency metrics are representative of word prevalence in print news media content (see Figure 1 in the main manuscript for illustration of the accuracy of the frequency counts).</p>

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Distribution. Brazil, S of the Rio Amazonas-Solimoes and W of the Rio TapajosJuruena to the right bank of the Rio Guaporé and the left (N) bank of the Rio Madre de Dios in N Bolivia, also in SE Peru W to the Rio Huallaga and N as far the Rio Cushabatay at about 07° S. in Aotidae

Distribution. Brazil, S of the Rio Amazonas-Solimoes and W of the Rio TapajosJuruena to the right bank of the Rio Guaporé and the left (N) bank of the Rio Madre de Dios in N Bolivia, also in SE Peru W to the Rio Huallaga and N as far the Rio Cushabatay at about 07° S.

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Distribution. Not well known, but includes S Venezuela (upper Orinoco Basin, limited by the Llanos/forest interface to the W and by the left bank of the Rio Caura in the E), NW Brazil (N of the Rio Solimoes as far as the mouth of the Rio Japura, E to the Rio Negro, throughout the region N of the Rio Negro and W of the Rio Branco in Amazonas and Roraimastates), E Colombia (in the piedmont of the Cordillera Oriental as far N as the Rio Upia drainage in Boyaca Department, including the region of Sierra de la Macarena, E Meta Department, and S to the Coehmani rapids of the Rio Caqueta in the SE of Caqueta Department; it is rare W of the Rio Yari and has been seen on the upper Rio Mesay, opposite the mouth of the Rio Pira-Parana on the right bank of the Rio Apaporis, and the lower right bank of the Apaporis), E Ecuador and NE Peru (restricted to the S of the Rio Napo, extending into N Peru between the rios Putumayo and Amazonas, along the left bank of the Rio Ucayali, and including the basins of the rios Napo, Tigre, Maranén, Pastaza, Pacaya, and Samiria, S as far as the Rio Cushabatay, a tributary of the Rio Ucayali). in Atelidae

Distribution. Not well known, but includes S Venezuela (upper Orinoco Basin, limited by the Llanos/forest interface to the W and by the left bank of the Rio Caura in the E), NW Brazil (N of the Rio Solimoes as far as the mouth of the Rio Japura, E to the Rio Negro, throughout the region N of the Rio Negro and W of the Rio Branco in Amazonas and Roraimastates), E Colombia (in the piedmont of the Cordillera Oriental as far N as the Rio Upia drainage in Boyaca Department, including the region of Sierra de la Macarena, E Meta Department, and S to the Coehmani rapids of the Rio Caqueta in the SE of Caqueta Department; it is rare W of the Rio Yari and has been seen on the upper Rio Mesay, opposite the mouth of the Rio Pira-Parana on the right bank of the Rio Apaporis, and the lower right bank of the Apaporis), E Ecuador and NE Peru (restricted to the S of the Rio Napo, extending into N Peru between the rios Putumayo and Amazonas, along the left bank of the Rio Ucayali, and including the basins of the rios Napo, Tigre, Maranén, Pastaza, Pacaya, and Samiria, S as far as the Rio Cushabatay, a tributary of the Rio Ucayali).

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Subspecies and Distribution. L. c. cana E. Geoffroy Saint-Hilaire, 1812 — Brazilian Amazon, S of the Rio Amazonas-Solimoes, between the rios Jurua and Tapajos-Juruena, but restricted to the left bank of the Rio Madeira above the mouth of the Rio Jiparana (a right bank tributary), and to the right bank of the Rio Jiparana, S to ¢.12° S, and W along the N (left bank) of the Rio Abuna on the upper Rio Madeira. L. c. tschudii Pucheran, 1857 — SE Peru, its range is poorly known butis believed to extend between the rios Pachitea and Ucayali, S from the Rio Inuya, W as far as the Rio Inambari, and S to both sides of the Rio Madre de Dios into the Rio Tambopata Basin, to the frontier with Bolivia, with an isolated population in Madidi National Park. in Atelidae

Subspecies and Distribution. L. c. cana E. Geoffroy Saint-Hilaire, 1812 — Brazilian Amazon, S of the Rio Amazonas-Solimoes, between the rios Jurua and Tapajos-Juruena, but restricted to the left bank of the Rio Madeira above the mouth of the Rio Jiparana (a right bank tributary), and to the right bank of the Rio Jiparana, S to ¢.12° S, and W along the N (left bank) of the Rio Abuna on the upper Rio Madeira. L. c. tschudii Pucheran, 1857 — SE Peru, its range is poorly known butis believed to extend between the rios Pachitea and Ucayali, S from the Rio Inuya, W as far as the Rio Inambari, and S to both sides of the Rio Madre de Dios into the Rio Tambopata Basin, to the frontier with Bolivia, with an isolated population in Madidi National Park.

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Distribution. SE Brazil (Sao Paulo State), along the N (right) margin of the Rio Paranapanema, W as far as the Rio Parana, and between the upper rios Paranapanema and Tieté; today, known only from eleven widely separated forest patches covering c.444 km". in Callitrichiade

Distribution. SE Brazil (Sao Paulo State), along the N (right) margin of the Rio Paranapanema, W as far as the Rio Parana, and between the upper rios Paranapanema and Tieté; today, known only from eleven widely separated forest patches covering c.444 km".

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Distribution. NE Peru, between the rios Amazonas and Yavari, to the right bank of the rios Ucayali and Tapiche as far as the Rio Blanco (upstream of the Rio Ucayali along both sides of the river, to the S of the Rio Blanco, it is replaced by S. illigeri), but it appears again on the right bank of the Rio Ucayali at the headwaters of the Rio Tapiche, a left bank tributary of the Rio Blanco, probably extending E as far as the Rio Yavari, on the border with Brazil. in Callitrichiade

Distribution. NE Peru, between the rios Amazonas and Yavari, to the right bank of the rios Ucayali and Tapiche as far as the Rio Blanco (upstream of the Rio Ucayali along both sides of the river, to the S of the Rio Blanco, it is replaced by S. illigeri), but it appears again on the right bank of the Rio Ucayali at the headwaters of the Rio Tapiche, a left bank tributary of the Rio Blanco, probably extending E as far as the Rio Yavari, on the border with Brazil.

opennotspecifiedMar 2013View details →
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Distribution. Brazilian Amazon and SE Colombia, between the upper Rio Negro and Rio Japura, W from opposite the Rio Padauari (64° W), N of the Rio Caqueta, E as far as the lower Rio Yari and the right bank of the Rio Mesay; it extends N through the Apaporis and Vaupés basins, possibly to the upper Rio Guaviare; N and W limits in Colombia are not known; not recorded in Venezuela. in Callitrichiade

Distribution. Brazilian Amazon and SE Colombia, between the upper Rio Negro and Rio Japura, W from opposite the Rio Padauari (64° W), N of the Rio Caqueta, E as far as the lower Rio Yari and the right bank of the Rio Mesay; it extends N through the Apaporis and Vaupés basins, possibly to the upper Rio Guaviare; N and W limits in Colombia are not known; not recorded in Venezuela.

opennotspecifiedMar 2013View details →
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Subspecies and Distribution. S. w. weddelli Deville, 1849 — W Brazil (between the rios Purus and Madeira in the states of Amazonas, Acre, and NW Rondonia, as far N as the Rio Pixuna) to SE Peru (from the Rio Abujao, E tributary of the Rio Ucayali, to the S along both banks of the Rio Ucayali, E of the Andes, E of the Rio Apurimac, and along the upper reaches of the Apurimac, Inambari, Urubamba, and Tambopata), and to N Bolivia (rios Madeira and Beni or Mamoré); it crosses the upper Rio Madeira to its right bank in Rondonia in the region of the Rio Jamari, S of the Rio Ji-parana, being sympatric there with Rondon's Marmoset (Mico rondonz). S. w. crandalli Hershkovitz, 1966 — provenance unknown but possibly near the headwaters of the rios Jurua and Tarauaca in W Brazil. S. w. melanoleucus Miranda Ribeiro, 1912 — Brazilian Amazon, along the right bank of the upper Rio Jurua, S from the mouth of the Rio Eira, up to its headwaters, E to the left bank of the Rio Tarauaca (no saddle-back tamarins have been recorded to the E of the Rio Tarauaca in Acre State as far as the upper Rio Purus), in SE Peru from the upper reaches of the Rio Breu and the Quebrada Breu, right bank affluents of the upper Rio Yurua. in Callitrichiade

Subspecies and Distribution. S. w. weddelli Deville, 1849 — W Brazil (between the rios Purus and Madeira in the states of Amazonas, Acre, and NW Rondonia, as far N as the Rio Pixuna) to SE Peru (from the Rio Abujao, E tributary of the Rio Ucayali, to the S along both banks of the Rio Ucayali, E of the Andes, E of the Rio Apurimac, and along the upper reaches of the Apurimac, Inambari, Urubamba, and Tambopata), and to N Bolivia (rios Madeira and Beni or Mamoré); it crosses the upper Rio Madeira to its right bank in Rondonia in the region of the Rio Jamari, S of the Rio Ji-parana, being sympatric there with Rondon's Marmoset (Mico rondonz). S. w. crandalli Hershkovitz, 1966 — provenance unknown but possibly near the headwaters of the rios Jurua and Tarauaca in W Brazil. S. w. melanoleucus Miranda Ribeiro, 1912 — Brazilian Amazon, along the right bank of the upper Rio Jurua, S from the mouth of the Rio Eira, up to its headwaters, E to the left bank of the Rio Tarauaca (no saddle-back tamarins have been recorded to the E of the Rio Tarauaca in Acre State as far as the upper Rio Purus), in SE Peru from the upper reaches of the Rio Breu and the Quebrada Breu, right bank affluents of the upper Rio Yurua.

opennotspecifiedMar 2013View details →
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Subspecies and Distribution. S. J. fuscicollis Spix, 1823 — W Brazil (states of Acre & Amazonas) and Peru, S of the Rio Solimoes, between the Rio Javari in the W, E through the Rio Jutai Basin to the Rio Jurua (left bank), also in Peru, W of the Rio Yavari as far as the Rio Tapiche, an E tributary of the Rio Ucayali, and extending N from there as far as the Rio Blanco (left bank), where it meets the distribution of Geoffroy's Saddle-back Tamarin, S. nigrifrons (right bank of the Rio Blanco). S. f. auvilapiresi Hershkovitz, 1966 — W Brazil in the Amazonas State (type locality is the mouth of the Lago de Tefé, Rio Solimoes), found along the S of the Rio Solimoes between the rios Jurua and Purus, including the basins of the rios Urucu and Coari, and probably the Rio Tefé; the S limits are not known but possibly in the region of the N bank of the Rio Tapaua, an affluent of the Rio Purus. S. f. eruzlimai Hershkovitz, 1966 — W Brazil, described by Hershkovitz without provenance (based on a single individual "said to be from the upper Rio Purus"); M. G. M. van Roosmalen reported in 2003 that it had been observed by T. van Roosmalen on 21 June 2002, on the W bank of the Rio Purus, opposite the mouth of the Rio Sepatini, and noted that Hershkovitz was correct in supposing that it occurred between the rios Pauini and Tapaua, W of the Rio Purus. S. J. mura Rohe et al, 2009 — C Brazil (Amazonas State), interfluvium of the rios Madeira and Purus, S of the Rio Amazonas, probably S to the Rio Igapo-Acu. S. f. primitivus Hershkovitz, 1977 — W Brazil (Amazonas State), the distribution is believed to extend from the left bank of the Rio Pauini, along the left bank of the upper Rio Purus, N to the Rio Tapaua (right bank), as far W the right bank of the Rio Jurua, and the Rio Tarauaca. in Callitrichiade

Subspecies and Distribution. S. J. fuscicollis Spix, 1823 — W Brazil (states of Acre &amp; Amazonas) and Peru, S of the Rio Solimoes, between the Rio Javari in the W, E through the Rio Jutai Basin to the Rio Jurua (left bank), also in Peru, W of the Rio Yavari as far as the Rio Tapiche, an E tributary of the Rio Ucayali, and extending N from there as far as the Rio Blanco (left bank), where it meets the distribution of Geoffroy's Saddle-back Tamarin, S. nigrifrons (right bank of the Rio Blanco). S. f. auvilapiresi Hershkovitz, 1966 — W Brazil in the Amazonas State (type locality is the mouth of the Lago de Tefé, Rio Solimoes), found along the S of the Rio Solimoes between the rios Jurua and Purus, including the basins of the rios Urucu and Coari, and probably the Rio Tefé; the S limits are not known but possibly in the region of the N bank of the Rio Tapaua, an affluent of the Rio Purus. S. f. eruzlimai Hershkovitz, 1966 — W Brazil, described by Hershkovitz without provenance (based on a single individual "said to be from the upper Rio Purus"); M. G. M. van Roosmalen reported in 2003 that it had been observed by T. van Roosmalen on 21 June 2002, on the W bank of the Rio Purus, opposite the mouth of the Rio Sepatini, and noted that Hershkovitz was correct in supposing that it occurred between the rios Pauini and Tapaua, W of the Rio Purus. S. J. mura Rohe et al, 2009 — C Brazil (Amazonas State), interfluvium of the rios Madeira and Purus, S of the Rio Amazonas, probably S to the Rio Igapo-Acu. S. f. primitivus Hershkovitz, 1977 — W Brazil (Amazonas State), the distribution is believed to extend from the left bank of the Rio Pauini, along the left bank of the upper Rio Purus, N to the Rio Tapaua (right bank), as far W the right bank of the Rio Jurua, and the Rio Tarauaca.

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Distribution. Poorly known, but it is believed to extend from the S (right) bank of the upper reaches of the Rio Purus in SE Peru, W into the Rio Urubamba Valley in the Cuzco Department, including the upper Rio Madre de Dios, S and E as far the Tambopata Basin, and extending into NW Bolivia. in Cebidae

Distribution. Poorly known, but it is believed to extend from the S (right) bank of the upper reaches of the Rio Purus in SE Peru, W into the Rio Urubamba Valley in the Cuzco Department, including the upper Rio Madre de Dios, S and E as far the Tambopata Basin, and extending into NW Bolivia.

opennotspecifiedMar 2013View details →
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Distribution. SW Amazon Basin in the states of Amazonas and Rondoénia, Brazil; little is known ofits distribution in the wild, although it is presumed to coincide with the Ipixuna-Mucuim interfluvium on the right (S) bank of the Rio Purus, possibly extending as far S as the Rio Madeira in Rondonia. in Phitheciidae

Distribution. SW Amazon Basin in the states of Amazonas and Rondoénia, Brazil; little is known ofits distribution in the wild, although it is presumed to coincide with the Ipixuna-Mucuim interfluvium on the right (S) bank of the Rio Purus, possibly extending as far S as the Rio Madeira in Rondonia.

opennotspecifiedMar 2013View details →

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

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