word
stringlengths
3
21
pos-tag
class label
4 classes
Abmachung
0NN
Abschluß
0NN
Abstimmung
0NN
Agilität
0NN
Aktivität
0NN
Aktualisierung
0NN
Aktualität
0NN
Akzeptanz
0NN
Andrang
0NN
Anerkennung
0NN
Angebot
0NN
Angemessenheit
0NN
Anhebung
0NN
Anheiterung
0NN
Ankurbelung
0NN
Annehmlichkeit
0NN
Annäherung
0NN
Anpassung
0NN
Anpassungsfähigkeit
0NN
Anreicherung
0NN
Anspruch
0NN
Anstand
0NN
Anstieg
0NN
Anständigkeit
0NN
Anteil
0NN
Anziehung
0NN
Applaus
0NN
Attraktivität
0NN
Aufbereitung
0NN
Aufbesserung
0NN
Auferstehung
0NN
Aufmerksamkeit
0NN
Aufmunterung
0NN
Aufrichtigkeit
0NN
Aufschwung
0NN
Aufstieg
0NN
Aufstockung
0NN
Auftrag
0NN
Auftrieb
0NN
Aufwertung
0NN
Aufwärtstrend
0NN
Augenweide
0NN
Ausbau
0NN
Ausbildung
0NN
Ausdauer
0NN
Ausgleich
0NN
Ausgleichszahlung
0NN
Auszeichnung
0NN
Authentizität
0NN
Autonomie
0NN
Bedeutung
0NN
Befreiung
0NN
Befriedigung
0NN
Beförderung
0NN
Begeisterung
0NN
Begnadigung
0NN
Begünstigung
0NN
Beifall
0NN
Beifallsruf
0NN
Beilegung
0NN
Beisteuerung
0NN
Beitritt
0NN
Bekräftigung
0NN
Belastbarkeit
0NN
Belebtheit
0NN
Beliebtheit
0NN
Belohnung
0NN
Benefiz
0NN
Bereicherung
0NN
Bereitschaft
0NN
Bereitstellung
0NN
Beruhigung
0NN
Bescheidenheit
0NN
Beschleunigung
0NN
Beschwichtigung
0NN
Besitz
0NN
Besserung
0NN
Bestätigung
0NN
Beteiligung
0NN
Bewunderer
0NN
Bewunderung
0NN
Bildung
0NN
Blüte
0NN
Bonität
0NN
Bonus
0NN
Boom
0NN
Brillanz
0NN
Brüderlichkeit
0NN
Bund
0NN
Bündnis
0NN
Champion
0NN
Charisma
0NN
Charme
0NN
Cleverness
0NN
Comeback
0NN
Dankbarkeit
0NN
Diskretion
0NN
Disziplin
0NN
Duft
0NN
Dynamik
0NN

Dataset Card for SentiWS

Dataset Summary

SentimentWortschatz, or SentiWS for short, is a publicly available German-language resource for sentiment analysis, opinion mining etc. It lists positive and negative polarity bearing words weighted within the interval of [-1; 1] plus their part of speech tag, and if applicable, their inflections. The current version of SentiWS contains around 1,650 positive and 1,800 negative words, which sum up to around 16,000 positive and 18,000 negative word forms incl. their inflections, respectively. It not only contains adjectives and adverbs explicitly expressing a sentiment, but also nouns and verbs implicitly containing one.

Supported Tasks and Leaderboards

Sentiment-Scoring, Pos-Tagging

Languages

German

Dataset Structure

Data Instances

For pos-tagging:

{ 
"word":"Abbau"
"pos_tag": 0
}

For sentiment-scoring:

{
"word":"Abbau"
"sentiment-score":-0.058
}

Data Fields

SentiWS is UTF8-encoded text. For pos-tagging:

  • word: one word as a string,
  • pos_tag: the part-of-speech tag of the word as an integer, For sentiment-scoring:
  • word: one word as a string,
  • sentiment-score: the sentiment score of the word as a float between -1 and 1,

The POS tags are ["NN", "VVINF", "ADJX", "ADV"] -> ["noun", "verb", "adjective", "adverb"], and positive and negative polarity bearing words are weighted within the interval of [-1, 1].

Data Splits

train: 1,650 negative and 1,818 positive words

Dataset Creation

Curation Rationale

[Needs More Information]

Source Data

Initial Data Collection and Normalization

[Needs More Information]

Who are the source language producers?

[Needs More Information]

Annotations

Annotation process

[Needs More Information]

Who are the annotators?

[Needs More Information]

Personal and Sensitive Information

[Needs More Information]

Considerations for Using the Data

Social Impact of Dataset

[Needs More Information]

Discussion of Biases

[Needs More Information]

Other Known Limitations

[Needs More Information]

Additional Information

Dataset Curators

[Needs More Information]

Licensing Information

Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported License

Citation Information

@INPROCEEDINGS{remquahey2010, title = {SentiWS -- a Publicly Available German-language Resource for Sentiment Analysis}, booktitle = {Proceedings of the 7th International Language Resources and Evaluation (LREC'10)}, author = {Remus, R. and Quasthoff, U. and Heyer, G.}, year = {2010} }

Contributions

Thanks to @harshalmittal4 for adding this dataset.

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