DOI: 10.5281/zenodo.7908392
title: NeMig - A Bilingual News Collection and Knowledge Graph about Migration

description: NeMig represents a bilingual news collection and knowledge graphs on the topic of migration. The news corpora in German and English were collected from online media outlets from Germany and the US, respectively. NeMIg contains rich textual and metadata information, sentiment and political orientation annotations, as well as named entities extracted from the articles' content and metadata and linked to Wikidata. The corresponding knowledge graphs (NeMigKG) built from each corpus are expanded with up to two-hop neighbors from Wikidata of the initial set of linked entities. NeMigKG comes in four flavors, for both the German, and the English corpora: Base NeMigKG: contains literals and entities from the corresponding annotated news corpus; Entities NeMigKG: derived from the Base NeMIg by removing all literal nodes, it contains only resource nodes; Enriched Entities NeMigKG: derived from the Entities NeMig by enriching it with up to two-hop neighbors from Wikidata, it contains only resource nodes and Wikidata triples; Complete NeMigKG: the combination of the Base and Enriched Entities NeMig, it contains both literals and resources. Information about uploaded files: (all files are b-zipped and in the N-Triples format.) A description of the <strong>NeMigKG files</strong> is provided in the table below: NeMigKG Files Description File Description nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-metadata.nt.bz2 Metadata about the dataset, described using void vocabulary. nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_types.nt.bz2 Class definitions of news and event instances. nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_labels.nt.bz2 Labels of instances. nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_related.nt.bz2 Relations between news instances based on one another. nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_metadata_literals.nt.bz2 Relations between news instances and metadata literals (e.g. URL, publishing date, modification date, sentiment label, political orientation of news outlets). nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_content_mapping.nt.bz2 Mapping of news instances to content instances (e.g. title, abstract, body). nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_topic_mapping.nt.bz2 Mapping of news instances to sub-topic instances. nemig_<em>${language</em>}_ <em>$</em>{<em>graph_type</em>}-instances_sentiment_mapping.nt.bz2 Mapping of news instances to sentiment classes. emig_<em>${language}</em>_ <em>${graph_type}</em>-instances_political_orientation_mapping.nt.bz2 Mapping of news outlets instances to political orientation classes. nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_content_literals.nt.bz2 Relations between content instances and corresponding literals (e.g. text of title, abstract, body). nemig_<em>${language}_ ${graph_type}</em>-instances_sentiment_polorient_literals.nt.bz2 Relations between instances and corresponding sentiment or political orientation literals. nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_metadata_resources.nt.bz2 Relations between news or sub-topic instances and entities extracted from metadata (i.e. publishers, authors, keywords). nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_event_mapping.nt.bz2 Mapping of news instances to event instances. nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-event_resources.nt.bz2 Relations between event instances and entities extracted from the text of the news (i.e. actors, places, mentions). nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-resources_provenance.nt.bz2 Provenance information about the entities extracted from the text of the news (e.g. title, abstract, body). nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-wiki_resources.nt.bz2 Relations between Wikidata entities from news and their <em>k</em>-hop entity neighbors from Wikidata. The corresponding user data has been collected through online studies in Germany and the US. We used the participants' implicit feedback regarding their interest in an article to build their click history, and the explicit feedback in terms of news click behaviors to construct the impression logs. To protect user privacy, we assign each user an anonymized ID. The German and English user datasets are zip-compressed folders, which contain two files each. NeMig User Dataset File Description <strong>File</strong> <strong>Description</strong> behaviors.tsv The click history and impression logs of users. demographics_politics.tsv Demographic and political information of users. The <strong>behaviors.tsv</strong> file contains the users' news click histories and the impression logs. It has 4 columns divided by the tab symbol: Impression ID: the ID of an impression. User ID: The anonymized ID of an user. Click History: The news click history (list of news IDs) of a user before an impression. Impression Log: List of news displayed to the user in a session and the user's click behavior on them (1 for click, 0 for non-click). The <strong>demographics_politics.tsv</strong> file contains detailed information about the users' demographics and political interests. It has columns divided by the tab symbol. An explanation of all the columns and the questions used in the online studies to collect this information is shown in the table below. Demographic and political user data description Column Name Question in German study Scale in German Question in English study Scale in English <strong>Demographics</strong> Gender Bitte geben Sie Ihr Geschlecht an 0 = männlich<br> 1 = weiblich<br> 2 = divers<br> 3 = Keine Angabe Please indicate your gender. 0 = male<br> 1 = female<br> 2 = other<br> 3 = no answer Age Bitte geben Sie Ihr Alter an 1-120 Please indicate your age. 1-120 Qualification Welches ist Ihr höchster Bildungsabschluss? 0 = Kein Schulabschluss<br> 1 = Haupt-/Gesamtschulabschluss<br> 2 = Realschulabschluss, Mittlere Reife, Fachschulreife<br> 3 = Fachhochschulreife, Abitur<br> 4 = Studium mit Abschluss<br> 5 = Promotion<br> 6 = Keine Angabe Please indicate your highest educational qualification. 0 = less than high school<br> 1 = high school/GED<br> 2 = Vo-tech/business school<br> 3 = some college<br> 4 = college degree<br> 5 = university degree<br> 6 = doctoral degree<br> 7 = no answer Nationality Welche Staatsangehörigkeit besitzen Sie? 0 = Nur die deutsche Staatsangehörigkeit<br> 1 = Die deutsche und eine andere Staatsangehörigkeit<br> 2 = Nur eine andere Staatsangehörigkeit<br> 3 = Keine Angabe What is your citizenship? 0 = U.S. citizenship<br> 1 = U.S. and another non-U.S. citizenship<br> 2 = Only non-U.S. citizenship<br> 3 = No Answer BornIn Sind Sie in Deutschland geboren? 0 = Ja<br> 1 = Nein<br> 2 = Keine Angabe Were you born in the U.S.? 0 = Yes<br> 1 = No<br> 2 = No answer ParentsBornIn Sind Ihre Eltern in Deutschland geboren? 0 = Mein Vater und meine Mutter sind beide in Deutschland geboren<br> 1 = Mein Vater ist in Deutschland geboren, meine Mutter nicht<br> 2 = Meine Mutter ist in Deutschland geboren, mein Vater nicht<br> 3 = Weder meine Mutter noch mein Vater sind in Deutschland geboren<br> 4 = Keine Angabe Were your parents born in the U.S.? 0 = My father and my mother were both born in the U.S.<br> 1 = My father was born in the U.S., my mother was not<br> 2 = My mother was born in the U.S., my father was not<br> 3 = Neither my mother nor my father were born in the U.S<br> 4 = No answer Income Was ist Ihr persönliches monatliches Nettoeinkommen (nach Abzug der Steuern)? Bitte geben Sie eine ungefähre Schätzung an, falls Sie die genaue Zahl nicht kennen. 0 = Weniger als 1000 €<br> 1 = 1001 € bis 2000 €<br> 2 = 2001 € bis 3000 €<br> 3 = 3001 € bis 4000 €<br> 4 = 4001 € bis 5000 €<br> 5 = Mehr als 5000 €<br> 6 = Keine Angabe What is your personal monthly net income (after taxes)? Please give an approximate estimation in case you are unsure. 0 = Less than 1000 $<br> 1 = 1001 $ to 2000 $<br> 2 = 2001 $ to 3000 $<br> 3 = 3001 $ to 4000 $<br> 4 = 4001 $ to 5000 $<br> 5 = More than 5000 $<br> 6 = No Answer <strong>Empathy</strong> <strong>Wie sehr stimmen Sie den folgenden Aussagen zu?</strong> <strong>7-point Likert scale</strong> <strong>1=Trifft überhaupt nicht zu<br> 7=Trifft voll und ganz zu</strong> <strong>How strongly do you agree with the following statements?</strong> <strong>7-point Likert scale<br> <br> 1=Strongly disagree<br> 7=Strongly agree</strong> EMP1 Wenn jemand anderes erfreut ist, tendiere ich dazu auch erfreut zu sein. When someone else is feeling excited, I tend to get excited too. EMP2 Es regt mich auf, wenn jemand respektlos behandelt wird. It upsets me to see someone being treated disrespectfully. EMP3 Es macht mir Freude, andere aufzumuntern. I enjoy making other people feel better. EMP4 Ich bin besorgt um Personen, die weniger Glück haben als ich. I have tender, concerned feelings for people less fortunate than me. EMP5 Ich fühle, wenn andere traurig sind, selbst wenn sie nichts sagen. I can tell when others are sad even when they do not say anything. EMP6 Meistens bin ich mit den Stimmungen anderer Leute im Einklang. I find that I am “in tune” with other people’s moods. EMP7 Ich empfinde einen starken Drang zu helfen, wenn ich jemanden sehe, der aufgebracht ist. I get a strong urge to help when I see someone who is upset. EMP8 Wenn ich jemanden sehe, der ausgenutzt wird, möchte ich die Person beschützen. When I see someone being taken advantage of, I feel kind of protective towards him\her. <strong>Big5</strong> <strong>Ich bin...</strong> <strong>7-point Likert scale</strong> <strong>0 = Sehr<br> 1 = Ziemlich<br> 2 = Etwas<br> 3 = Teils=Teils<br> 4 = Etwas<br> 5 = Zeimlich<br> 6 = Sehr</strong> <strong>I see myself as...</strong> <strong>7-point Likert scale</strong> <strong>1=Strongly disagree<br> 7=Strongly agree</strong> BIG1 extrovertiert -- introvertiert ...extroverted, enthusiastic BIG2 emotional -- ausgeglichen ...critical, quarrelsome BIG3 aufgeschlossen -- festgelegt ...dependable, self-disciplined BIG4 barsch -- umgänglich ...anxious, easily upset BIG5 gewissenhaft -- nachlässig ...open to new experiences, complex BIG6 - ...reserved, quiet BIG7 - ...sympathetic, warm BIG8 - ...disorganized, careless BIG9 - ..calm, emotionally stable BIG10 - ...conventional, uncreative <strong>Ideological Polarization</strong> <strong>Im Folgenden sehen Sie eine Reihe von gegensätzlichen Aussagen.<br> Bitte geben Sie jeweils an, wie sehr Sie der Aussage zustimmen oder diese ablehnen.<br> Es gibt keine richtigen oder falschen Antworten.</strong> <strong>7-point Likert scale</strong> <strong>0 = Sehr<br> 1 = Ziemlich<br> 2 = Etwas<br> 3 = Teils=Teils<br> 4 = Etwas<br> 5 = Zeimlich<br> 6 = Sehr</strong> <strong>In the following, you will see a series of opposing statements.<br> Please indicate how strongly you agree or disagree with the statements.<br> There are no right or wrong answers.</strong> <strong>7-point Likert scale</strong> <strong>1=Strongly disagree<br> 7=Strongly agree</strong> IPO1 Deutschland sollte mehr Geflüchtete aufnehmen. The U.S. should take in more refugees. IPO2 Deutschland hat schon zu viele Flüchtlinge aufgenommen. The U.S. should take in more refugees. IPO3 Deutschland sollte sich für sichere und einfache Fluchtwege nach Europa einsetzen. The U.S. should advocate safe and easy escape routes to North America. IPO4 Deutschland sollte sich dafür einsetzen, dass Flüchtlinge nicht einfach nach Europa kommen können. The U.S. should work to ensure that refugees cannot easily come to North America. IPO5 Immigranten bemühen sich um ein friedliches Zusammenleben mit Deutschen. Immigrants strive for peaceful cohabitation with U.S.-Americans. IPO6 Immigranten treten den Deutschen feindselig gegenüber. Immigrants are hostile toward U.S.-Americans. IPO7 Immigranten wollen auf Kosten des deutschen Wohlstands leben. Immigrants want to live at the expense of U.S.-American prosperity. IPO8 Immigranten helfen dabei, den deutschen Wohlstand zu sichern. Immigrants help in securing U.S.-American prosperity. IPO9 Immigranten bedrohen die deutsche Kultur und Lebensweise. Immigrants threaten the U.S.-American culture and lifestyle. IPO10 Immigranten bereichern die deutsche Kultur und Lebensweise. Immigrants enrich the U.S.-American culture and lifestyle. IPO11 Immigranten sind krimineller und gewalttätiger als Deutsche. Immigrants are more criminal and more violent than U.S.-Americans. IPO12 Immigranten sind nicht krimineller oder gewalttätiger als Deutsche. Immigrants are not more criminal and violent than U.S.-Americans. <strong>Emotions</strong> <strong>Welche Emotionen empfinden Sie gegenüber Geflüchteten und Immigranten in Deutschland?</strong> <strong>7-point Likert Scale<br> <br> 1 = Stimme überhaupt nicht zu<br> 7 = Stimme voll zu</strong> <strong>Which emotions do you feel towards refugees and immigrants in the USA?</strong> <strong>7-point Likert Scale<br> <br> 1=Strongly disagree<br> 7=Strongly agree</strong> EMO1 Wut Anger EMO2 Angst Fear EMO3 Verachtung Contempt EMO4 Trauer Grief EMO5 Ekel Disgust EMO6 Neid Envy EMO7 Schadenfreude