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Register a new userTo Protect and To Serve? Analyzing Entity-Centric Framing of Police Violence
للحماية والخدمة؟تحليل تأطير الكيانات العنف للشرطة
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التأطير له تأثيرات كبيرة ولكن خفية على الرأي العام والسياسة.نقترح إطار NLP لقياس إطارات التركيز للكيان.نستخدمها لفهم التغطية الإعلامية حول أعمال عنف الشرطة في الولايات المتحدة في إطارات أعمال عنف جديدة من أعمال شرطة تضم 82 ألف مقالة إخبارية تمتد من عمليات قتل الشرطة 7K.لا يكشف عملنا عن أكثر من عشرة أجهزة تأطير ويكشف عن اختلافات كبيرة في طريقة تأكيد مصادر الأخبار الليبرالية والمحافظة مسألة أعمال عنف الشرطة والكيانات المعنية.تؤكد مصادر محافظة متى تكون الضحية مسلحة أو مهاجمة ضابط وأكثر عرضة للإبلاغ عن السجل الجنائي للضحية.تركز المصادر الليبرالية أكثر على الظلم النظامي الأساسي، مما يبرز عرق الضحية وأنهم غير مسلحين.نكتشف المسامير المؤقتة في هذه الإطارات الظلم بالقرب من أحداث إطلاق النار رفيعة المستوى، وأخيرا، نعرض حجم الاحتجاج يرتبط بقرارات تأطير وسائل الإعلام وتسبقها.
Framing has significant but subtle effects on public opinion and policy. We propose an NLP framework to measure entity-centric frames. We use it to understand media coverage on police violence in the United States in a new Police Violence Frames Corpus of 82k news articles spanning 7k police killings. Our work uncovers more than a dozen framing devices and reveals significant differences in the way liberal and conservative news sources frame both the issue of police violence and the entities involved. Conservative sources emphasize when the victim is armed or attacking an officer and are more likely to mention the victim's criminal record. Liberal sources focus more on the underlying systemic injustice, highlighting the victim's race and that they were unarmed. We discover temporary spikes in these injustice frames near high-profile shooting events, and finally, we show protest volume correlates with and precedes media framing decisions.
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Women is the half of society, which born and grow the second half, so take-up the oppression on women men to take-up it on whole society , because the women is the whole society, so the freedom of women is the freedom of country and human, where the
thrall mother cannot born freedom child , and sick mother cannot born healthy body, and mind child, so we must be attention toward necessary care of women ,and create suitable climant ,which help her to egress from the crucible of blindness, and darkness toward the court of science , and light supply the suitable circumstance, which command her to developed herself , and subsequently to developed the whole society, so man must stop to uses the Violence against women, because these thing disrupt her capability to life, and to feel her dignity, and humanity, but if he did not belief in these thing ,so we must constraint him by all possible procedure ,or methods.
The framing of political issues can influence policy and public opinion. Even though the public plays a key role in creating and spreading frames, little is known about how ordinary people on social media frame political issues. By creating a new dat
aset of immigration-related tweets labeled for multiple framing typologies from political communication theory, we develop supervised models to detect frames. We demonstrate how users' ideology and region impact framing choices, and how a message's framing influences audience responses. We find that the more commonly-used issue-generic frames obscure important ideological and regional patterns that are only revealed by immigration-specific frames. Furthermore, frames oriented towards human interests, culture, and politics are associated with higher user engagement. This large-scale analysis of a complex social and linguistic phenomenon contributes to both NLP and social science research.
In this paper, we measure variation in framing as a function of foregrounding and backgrounding in a co-referential corpus with a range of temporal distance. In one type of experiment, frame-annotated corpora grouped under event types were contrasted
, resulting in a ranking of frames with typicality rates. In contrasting between publication dates, a different ranking of frames emerged for documents that are close to or far from the event instance. In the second type of analysis, we trained a diagnostic classifier with frame occurrences in order to let it differentiate documents based on their temporal distance class (close to or far from the event instance). The classifier performs above chance and outperforms models with words.
Violence is clear in the story works of Zakarayya Tamer. It signifies most of his
works forming a chracteristict that distinguishes his own works from other written works
in this age and he proved himself a popular different writer who has his way
stating with
cursing and ending in crime regadless to his issues concerning (family, street,power) even
if they are different if we think of circumastances which lead to this colour of writing. In
this world the scenes of troublesome, fighting, raping and killing.
Thus violence signifies this world in which it is difficult to live out of desire to
blood by killing in the most terrified way seprating heads. This describes his way of
revealing the disasterous sort of writing away from the causes of these problematic affairs
which go deeper than what we are expecting. This is what the search is trying to deal with
and focus.
Much recent work in bilingual lexicon induction (BLI) views word embeddings as vectors in Euclidean space. As such, BLI is typically solved by finding a linear transformation that maps embeddings to a common space. Alternatively, word embeddings may
be understood as nodes in a weighted graph. This framing allows us to examine a node's graph neighborhood without assuming a linear transform, and exploits new techniques from the graph matching optimization literature. These contrasting approaches have not been compared in BLI so far. In this work, we study the behavior of Euclidean versus graph-based approaches to BLI under differing data conditions and show that they complement each other when combined. We release our code at https://github.com/kellymarchisio/euc-v-graph-bli.
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